Designing Internet Research (Winter 2020): Difference between revisions

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* Describe particular challenges and threats to research validity associated with each method.
* Describe particular challenges and threats to research validity associated with each method.
* For at least one method, be able to provide a detailed description of a research project and feel comfortable embarking on a formative study using this methodology.
* For at least one method, be able to provide a detailed description of a research project and feel comfortable embarking on a formative study using this methodology.
* Given a manuscript (e.g., in the context of a request for peer review), be able to evaluate a Internet-based study in terms of its use its methodological choices.
* Given a manuscript (e.g., in the context of a request for peer review), be able to evaluate an Internet-based study in terms of its use its methodological choices.
* Use a modern programming language (like Python) to collect a dataset from a web API like those published by Twitter, Reddit, or Wikipedia.
* Use a modern programming language (like Python) to collect a dataset from a web API like those published by Twitter, Reddit, or Wikipedia.


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=== Participation ===
=== Participation ===


The course relies heavily on participation and discussion. It is important to realize that we will not summarize reading in class and I will not cover it in lecture. I expect you all to have read it and we will jump in and start discussing it. The "Participation Rubric" section of [https://mako.cc/teaching/assessment.html my detailed page on assessment] gives the rubric I will use in evaluating participation.
The course relies heavily on participation and discussion. It is important to realize that we will not summarize reading in class and I will not cover it in lecture. I expect you all to have read it and we will jump in and start discussing it. The "Participation Rubric" section of [[User:Benjamin Mako Hill/Assessment| my detailed page on assessment]] gives the rubric I will use in evaluating participation.


=== Assessment ===
=== Assessment ===


I have put together a very detailed page that describes [[Assessment|the way I approach assessment and grading]]—both in general and in this course. Please read it carefully I will assign grades for each of following items on the UW 4.0 grade scale according to the weights below:
I have put together a very detailed page that describes [[User:Benjamin Mako Hill/Assessment|the way I approach assessment and grading]]—both in general and in this course. Please read it carefully I will assign grades for each of following items on the UW 4.0 grade scale according to the weights below:


* Participation: 30%
* Participation: 30%
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* boyd, danah. 2015. “Making Sense of Teen Life: Strategies for Capturing Ethnographic Data in a Networked Era.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig. Cambridge, Massachusetts: MIT Press. ''[[https://canvas.uw.edu/files/61411386/download?download_frd=1 Available in Canvas]]''
* boyd, danah. 2015. “Making Sense of Teen Life: Strategies for Capturing Ethnographic Data in a Networked Era.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig. Cambridge, Massachusetts: MIT Press. ''[[https://canvas.uw.edu/files/61411386/download?download_frd=1 Available in Canvas]]''
: Note: Strongly focused on enthnographic interviews with tons of very specific details. Fantastic article on interviewing, although perhaps a bit weak on Internet specific advice.
: Note: Strongly focused on ethnographic interviews with tons of very specific details. Fantastic article on interviewing, although perhaps a bit weak on Internet-specific advice.
* Markham, Annette N. 1998. “The Shifting Project, The Shifting Self.” In Life Online: Researching Real Experience in Virtual Space, 61–83. Rowman Altamira. ''[Available from instructor]''
* Markham, Annette N. 1998. “The Shifting Project, The Shifting Self.” In Life Online: Researching Real Experience in Virtual Space, 61–83. Rowman Altamira. ''[Available from instructor]''
: Note: One of the earliest books on online life and one of the earliest attempts to do online interviewing. This is dated, but highlight some important challenge.
: Note: One of the earliest books on online life and one of the earliest attempts to do online interviewing. This is dated, but highlight some important challenge.
* Hutchinson, Emma. 2016. “Digital Methods and Perpetual Reinvention? Asynchronous Interviewing and Photo Elicitation.” In Digital Methods for Social Science: An Interdisciplinary Guide to Research Innovation, edited by Helene Snee, Christine Hine, Yvette Morey, Steven Roberts, and Hayley Watson, 143–56. London: Palgrave Macmillan UK. https://doi.org/10.1057/9781137453662_9. ''[[https://doi.org/10.1057/9781137453662_9 Available through UW libraries]]''
* Hutchinson, Emma. 2016. “Digital Methods and Perpetual Reinvention? Asynchronous Interviewing and Photo Elicitation.” In Digital Methods for Social Science: An Interdisciplinary Guide to Research Innovation, edited by Helene Snee, Christine Hine, Yvette Morey, Steven Roberts, and Hayley Watson, 143–56. London: Palgrave Macmillan UK. https://doi.org/10.1057/9781137453662_9. ''[[https://doi.org/10.1057/9781137453662_9 Available through UW Libraries]]''
* Hawkins, Janice. 2018. “The Practical Utility and Suitability of Email Interviews in Qualitative Research.” The Qualitative Report 23 (2). https://digitalcommons.odu.edu/nursing_fac_pubs/24. ''[[https://digitalcommons.odu.edu/nursing_fac_pubs/24 Available free online]]''
* Hawkins, Janice. 2018. “The Practical Utility and Suitability of Email Interviews in Qualitative Research.” The Qualitative Report 23 (2). https://digitalcommons.odu.edu/nursing_fac_pubs/24. ''[[https://digitalcommons.odu.edu/nursing_fac_pubs/24 Available free online]]''


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=== Week 4: Saturday February 1: CDSW Session 2 ===
=== Week 4: Saturday February 1: CDSW Session 2 ===


As description in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the [[Community Data Science Workshops (Winter 2020)]] which I am running concurrently with this class.
As described in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the [[Community Data Science Workshops (Winter 2020)]] which I am running concurrently with this class.


This session will run from 10am-4pm. Details on the [[CDSW Winter 2020]] page.
This session will run from 10 am-4 pm. Details on the [[CDSW Winter 2020]] page.


=== Week 5: Tuesday February 4: (I) Surveys and (II) Experiments ===
=== Week 5: Tuesday February 4: (I) Surveys and (II) Experiments ===
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* Salganik, Matthew J., and Karen E. C. Levy. 2015. “Wiki Surveys: Open and Quantifiable Social Data Collection.” PLOS ONE 10 (5): e0123483. https://doi.org/10.1371/journal.pone.0123483. ''[[https://doi.org/10.1371/journal.pone.0123483 Free online]]''
* Salganik, Matthew J., and Karen E. C. Levy. 2015. “Wiki Surveys: Open and Quantifiable Social Data Collection.” PLOS ONE 10 (5): e0123483. https://doi.org/10.1371/journal.pone.0123483. ''[[https://doi.org/10.1371/journal.pone.0123483 Free online]]''
: Note: [http://www.technologyreview.com/view/531696/inspired-by-wikipedia-social-scientists-create-a-revolution-in-online-surveys/ This journalistic account of the research] may also be useful.
: Note: [http://www.technologyreview.com/view/531696/inspired-by-wikipedia-social-scientists-create-a-revolution-in-online-surveys/ This journalistic account of the research] may also be useful.
* Alperin, Juan Pablo, Erik Warren Hanson, Kenneth Shores, and Stefanie Haustein. 2017. “Twitter Bot Surveys: A Discrete Choice Experiment to Increase Response Rates.” In Proceedings of the 8th International Conference on Social Media & Society, 1–4. #SMSociety17. Toronto, ON, Canada: Association for Computing Machinery. https://doi.org/10.1145/3097286.3097313. ''[[https://doi.org/10.1145/3097286.3097313 Available through UW libraries]]'
* Alperin, Juan Pablo, Erik Warren Hanson, Kenneth Shores, and Stefanie Haustein. 2017. “Twitter Bot Surveys: A Discrete Choice Experiment to Increase Response Rates.” In Proceedings of the 8th International Conference on Social Media & Society, 1–4. #SMSociety17. Toronto, ON, Canada: Association for Computing Machinery. https://doi.org/10.1145/3097286.3097313. ''[[https://doi.org/10.1145/3097286.3097313 Available through UW libraries]]''


'''Optional Readings:'''
'''Optional Readings:'''
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* Krosnick, Jon A. 1999. “Maximizing Measurement Quality: Principles of Good Questionnaire Design.” In Measures of Political Attitudes, edited by John P. Robinson, Phillip R. Shaver, and Lawrence S. Wrightsman. New York: Academic Press.
* Krosnick, Jon A. 1999. “Maximizing Measurement Quality: Principles of Good Questionnaire Design.” In Measures of Political Attitudes, edited by John P. Robinson, Phillip R. Shaver, and Lawrence S. Wrightsman. New York: Academic Press.
* Krosnick, Jon A. 1999. “Survey Research.” Annual Review of Psychology 50 (1): 537–67. https://doi.org/10.1146/annurev.psych.50.1.537. ''[[https://doi.org/10.1146/annurev.psych.50.1.537 Available through UW libraries]]''
* Krosnick, Jon A. 1999. “Survey Research.” Annual Review of Psychology 50 (1): 537–67. https://doi.org/10.1146/annurev.psych.50.1.537. ''[[https://doi.org/10.1146/annurev.psych.50.1.537 Available through UW libraries]]''
Tools for doing mobile surveys:
* [https://www.rapidsms.org/ RapidSMS]
* [https://www.twilio.com/ Twilio]


==== Part II: Experiments ====
==== Part II: Experiments ====
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'''Required Readings:'''
'''Required Readings:'''


* Reips, Ulf-Dietrich. 2002. “Standards for Internet-Based Experimenting.” Experimental Psychology 49 (4): 243–56. https://doi.org/10.1026//1618-3169.49.4.243. ''[[https://doi.org/10.1026//1618-3169.49.4.243 Available through UW libraries]]'
* Reips, Ulf-Dietrich. 2002. “Standards for Internet-Based Experimenting.” Experimental Psychology 49 (4): 243–56. https://doi.org/10.1026//1618-3169.49.4.243. ''[[https://doi.org/10.1026//1618-3169.49.4.243 Available through UW Libraries]]'
* Salganik, Matthew J., Peter Sheridan Dodds, and Duncan J. Watts. 2006. “Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market.” Science 311 (5762): 854–56. https://doi.org/10.1126/science.1121066. ''[[https://doi.org/10.1126/science.1121066 Available through UW libraries]]'
* Salganik, Matthew J., Peter Sheridan Dodds, and Duncan J. Watts. 2006. “Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market.” Science 311 (5762): 854–56. https://doi.org/10.1126/science.1121066. ''[[https://doi.org/10.1126/science.1121066 Available through UW Libraries]]'
* Hergueux, Jérôme, and Nicolas Jacquemet. 2014. “Social Preferences in the Online Laboratory: A Randomized Experiment.” Experimental Economics 18 (2): 251–83. https://doi.org/10.1007/s10683-014-9400-5. ''[[https://doi.org/10.1007/s10683-014-9400-5 Available in Canvas]]''
* Hergueux, Jérôme, and Nicolas Jacquemet. 2014. “Social Preferences in the Online Laboratory: A Randomized Experiment.” Experimental Economics 18 (2): 251–83. https://doi.org/10.1007/s10683-014-9400-5. ''[[https://doi.org/10.1007/s10683-014-9400-5 Available in Canvas]]''
* Rijt, Arnout van de, Soong Moon Kang, Michael Restivo, and Akshay Patil. 2014. “Field Experiments of Success-Breeds-Success Dynamics.” Proceedings of the National Academy of Sciences 111 (19): 6934–39. https://doi.org/10.1073/pnas.1316836111. ''[[https://doi.org/10.1073/pnas.1316836111 Available in Canvas]]''
* Rijt, Arnout van de, Soong Moon Kang, Michael Restivo, and Akshay Patil. 2014. “Field Experiments of Success-Breeds-Success Dynamics.” Proceedings of the National Academy of Sciences 111 (19): 6934–39. https://doi.org/10.1073/pnas.1316836111. ''[[https://doi.org/10.1073/pnas.1316836111 Available in Canvas]]''
* Narayan, Sneha, Nathan TeBlunthuis, Wm Salt Hale, Benjamin Mako Hill, and Aaron Shaw. 2019. “All Talk: How Increasing Interpersonal Communication on Wikis May Not Enhance Productivity.” Proceedings of the ACM on Human-Computer Interaction 3 (CSCW): 101:1–101:19. https://doi.org/10.1145/3359203. ''[[https://doi.org/10.1145/3359230 Available through UW libraries]]'
* Narayan, Sneha, Nathan TeBlunthuis, Wm Salt Hale, Benjamin Mako Hill, and Aaron Shaw. 2019. “All Talk: How Increasing Interpersonal Communication on Wikis May Not Enhance Productivity.” Proceedings of the ACM on Human-Computer Interaction 3 (CSCW): 101:1–101:19. https://doi.org/10.1145/3359203. ''[[https://doi.org/10.1145/3359203 Available through UW Libraries]]'


'''Optional Readings:'''
'''Optional Readings:'''
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* Zhu, Haiyi, Amy Zhang, Jiping He, Robert E. Kraut, and Aniket Kittur. 2013. “Effects of Peer Feedback on Contribution: A Field Experiment in Wikipedia.” In , 2253. ACM Press. https://doi.org/10.1145/2470654.2481311. ''[[https://doi.org/10.1145/2470654.2481311 Available through UW libraries]]'
* Zhu, Haiyi, Amy Zhang, Jiping He, Robert E. Kraut, and Aniket Kittur. 2013. “Effects of Peer Feedback on Contribution: A Field Experiment in Wikipedia.” In , 2253. ACM Press. https://doi.org/10.1145/2470654.2481311. ''[[https://doi.org/10.1145/2470654.2481311 Available through UW libraries]]'
* Zhang, Xiaoquan (Michael), and Feng Zhu. 2011. “Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia.” American Economic Review 101 (4): 1601–15. https://doi.org/10.1257/aer.101.4.1601. ''[[https://doi.org/10.1257/aer.101.4.1601 Available through UW libraries]]'
* Zhang, Xiaoquan (Michael), and Feng Zhu. 2011. “Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia.” American Economic Review 101 (4): 1601–15. https://doi.org/10.1257/aer.101.4.1601. ''[[https://doi.org/10.1257/aer.101.4.1601 Available through UW libraries]]'
* Weninger, Tim, Thomas James Johnston, and Maria Glenski. 2015. “Random Voting Effects in Social-Digital Spaces: A Case Study of Reddit Post Submissions.” Pp. 293–297 in Proceedings of the 26th ACM Conference on Hypertext & Social Media, HT ’15. Guzelyurt, Northern Cyprus: Association for Computing Machinery.


=== Week 6: Tuesday February 11: (I) Crowdsourcing (II) Discourse Analysis ===
=== Week 6: Tuesday February 11: Crowdsourcing, Digital Labor Markets, and Human Computation ===
==== Part I: (I) Crowdsourced Data Analysis and Experimentation ====


'''Assignment:'''
:'''Note:''' I've marked things as '''[Required]''' below if they are required because I thought it made more sense to keep the topics groups of articles below intact.


* Find and complete at least 2 "hits" as a worker on [http://mturk.com Amazon Mechnical Turk]. Note that to do this you will need to create a ''worker'' account on Mturk.
MTurk documentation and guidelines:
** Record (write down) details and notes about your tasks: What did you do? Who was the requester? What could you was the purpose of the task (as best you could tell)? What was the experience like? What research applications can you (not) imagine for this kind of system?
* Design and deploy a small-scale research task on Mturk. Note that to do this, you will need to create a ''requester'' account on Mturk. Be sure to allow some time to get the task design the way you want it! Some ideas for study designs you might do:
** A small survey.
** Classification of texts or images (e.g., label tweets, pictures, or comments from a discussion thread).
** A small experiment (e.g., you can do a survey where you insert ''different'' images and ask the same set of questions. Check out the [https://requester.mturk.com/help/getting_started.html Mturk requester getting started guide]
* Prepare to share details of your small-scale research task in class, including results (they will come fast).


''Note:'' In terms of running your task, it will cost real money and you have to put money on your Amazon account yourself. You've each got a $3 budget. Please use your credit card to put $3 on your account right away. I will pay each of you $3 in cash next week to reimburse you for the cost of running the experiment.
* '''[Required]''' [https://docs.aws.amazon.com/AWSMechTurk/latest/RequesterUI/Introduction.html Amazon Mechanical Turk Requester UI Guide] — ''Skim, but make sure you're ready to submit tasks.''
* '''[Required]''' [https://mturkpublic.s3.amazonaws.com/docs/MTURK_BP.pdf Amazon Mechanical Turk Best Practices Guide] — ''Skim, but make sure you're ready to submit tasks.''
* '''[Required]''' Shaw, Aaron. 2015. “Hired Hands and Dubious Guesses: Adventures in Crowdsourced Data Collection.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig. The MIT Press. ''[[https://canvas.uw.edu/files/61787315/download?download_frd=1 Available in Canvas]]''
* '''[Required]''' [https://blog.mturk.com/tutorials/home Tutorials Posted on the MTurk blog] — ''Skim and browse and pay attention to things that are like what you'd like to do in the class session.''
* '''[Required]''' [https://wearedynamo.fandom.com/wiki/Guidelines_for_Academic_Requesters Guidelines for Academic Requesters] and [https://wearedynamo.fandom.com/wiki/Basics_of_how_to_be_a_good_requester Basics of How to be a good Requester] from the ''We Are Dynamo'' — These sets of guidelines were created by Turkers as part of an effort to engage in collective actions and organizer of Turkers run by Niloufar Saleh in the paper below.
* Mason, Winter, and Siddharth Suri. 2011. “Conducting Behavioral Research on Amazon’s Mechanical Turk.” Behavior Research Methods 44 (1): 1–23. https://doi.org/10.3758/s13428-011-0124-6. {{avail-uw|https://doi.org/10.3758/s13428-011-0124-6}} — ''Dated but still somewhat useful.''


'''Required Readings:'''
Overviews of MTurk and issues of data quality:
 
* Horton, John J., David G. Rand, and Richard J. Zeckhauser. 2011. “The Online Laboratory: Conducting Experiments in a Real Labor Market.” Experimental Economics 14 (3): 399–425. https://doi.org/10.1007/s10683-011-9273-9. {{avail-uw|https://doi.org/10.1007/s10683-011-9273-9}}
* Buhrmester, Michael, Tracy Kwang, and Samuel D. Gosling. 2011. “Amazon’s Mechanical Turk: A New Source of Inexpensive, yet High-Quality, Data?” Perspectives on Psychological Science, February. https://doi.org/10.1177/1745691610393980. {{avail-uw|https://doi.org/10.1177/1745691610393980}}
* Casler, Krista, Lydia Bickel, and Elizabeth Hackett. 2013. “Separate but Equal? A Comparison of Participants and Data Gathered via Amazon’s MTurk, Social Media, and Face-to-Face Behavioral Testing.” Computers in Human Behavior 29 (6): 2156–60. https://doi.org/10.1016/j.chb.2013.05.009. {{avail-uw|https://doi.org/10.1016/j.chb.2013.05.009}}
* '''[Required]''' Weinberg, Jill, Jeremy Freese, and David McElhattan. 2014. “Comparing Data Characteristics and Results of an Online Factorial Survey between a Population-Based and a Crowdsource-Recruited Sample.” Sociological Science 1: 292–310. https://doi.org/10.15195/v1.a19. {{avail-free|https://doi.org/10.15195/v1.a19}}
* Kees, Jeremy, Christopher Berry, Scot Burton, and Kim Sheehan. 2017. “An Analysis of Data Quality: Professional Panels, Student Subject Pools, and Amazon’s Mechanical Turk.” Journal of Advertising 46 (1): 141–55. https://doi.org/10.1080/00913367.2016.1269304. {{avail-uw|https://doi.org/10.1080/00913367.2016.1269304}}
* '''[Required]''' Kennedy, Ryan, Scott Clifford, Tyler Burleigh, Ryan Jewell, and Philip Waggoner. 2018. “The Shape of and Solutions to the MTurk Quality Crisis.” SSRN Scholarly Paper ID 3272468. Rochester, NY: Social Science Research Network. https://papers.ssrn.com/abstract=3272468. ''[[https://papers.ssrn.com/abstract=3272468 Available free online]]''
 
Culture and work conditions for Turkers:
 
* Irani, Lilly. 2015. “The Cultural Work of Microwork.” New Media & Society 17 (5): 720–39. https://doi.org/10.1177/1461444813511926. {{avail-uw|https://doi.org/10.1177/1461444813511926}}
* Kittur, Aniket, Jeffrey V. Nickerson, Michael Bernstein, Elizabeth Gerber, Aaron Shaw, John Zimmerman, Matt Lease, and John Horton. 2013. “The Future of Crowd Work.” In Proceedings of the 2013 Conference on Computer Supported Cooperative Work, 1301–1318. CSCW ’13. San Antonio, Texas, USA: Association for Computing Machinery. https://doi.org/10.1145/2441776.2441923. {{avail-uw|https://doi.org/10.1145/2441776.2441923}}  {{avail-free|http://hci.stanford.edu/publications/2013/CrowdWork/futureofcrowdwork-cscw2013.pdf}}
* Gray, Mary L., Siddharth Suri, Syed Shoaib Ali, and Deepti Kulkarni. 2016. “The Crowd Is a Collaborative Network.” In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 134–147. CSCW ’16. San Francisco, California, USA: Association for Computing Machinery. https://doi.org/10.1145/2818048.2819942. {{avail-uw|https://doi.org/10.1145/2818048.2819942}}
* '''[Required]''' Semuels, Alana. 2018. “The Internet Is Enabling a New Kind of Poorly Paid Hell.” The Atlantic. January 23, 2018. https://www.theatlantic.com/business/archive/2018/01/amazon-mechanical-turk/551192/. {{avail-free|https://www.theatlantic.com/business/archive/2018/01/amazon-mechanical-turk/551192/}}
 
Systems to approve Turker experiences:
 
* Salehi, Niloufar, Lilly C. Irani, Michael S. Bernstein, Ali Alkhatib, Eva Ogbe, Kristy Milland, and Clickhappier. 2015. “We Are Dynamo: Overcoming Stalling and Friction in Collective Action for Crowd Workers.” In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1621–1630. CHI ’15. Seoul, Republic of Korea: Association for Computing Machinery. https://doi.org/10.1145/2702123.2702508. {{avail-uw|https://doi.org/10.1145/2702123.2702508}}
* Irani, Lilly C., and M. Six Silberman. 2013. “Turkopticon: Interrupting Worker Invisibility in Amazon Mechanical Turk.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 611–620. CHI ’13. Paris, France: Association for Computing Machinery. https://doi.org/10.1145/2470654.2470742. {{avail-uw|https://doi.org/10.1145/2470654.2470742}}


* [https://docs.aws.amazon.com/AWSMechTurk/latest/RequesterUI/Introduction.html Amazon Mechanical Turk Requester UI Guide] ''[Free Online]''
'''Assignments to complete before class:'''
* [https://mturkpublic.s3.amazonaws.com/docs/MTURK_BP.pdf Amazon Mechanical Turk Best Practices Guide]. ''[Free Online]''
* Weinberg, J., Freese, J., & McElhattan, D. (2014). [https://www.sociologicalscience.com/articles-vol1-19-292/ Comparing Data Characteristics and Results of an Online Factorial Survey between a Population-Based and a Crowdsource-Recruited Sample]. Sociological Science, 1, 292–310. ''[Free Online]''
* Shaw, A. (2015). [https://canvas.uw.edu/files/36419326/download?download_frd=1 Hired Hands and Dubious Guesses: Adventures in Crowdsourced Data Collection]. In E. Hargittai & C. Sandvig (Eds.), Digital Research Confidential: The Secrets of Studying Behavior Online. The MIT Press. ''[Available in Canvas]''


'''Optional Readings:'''
The first task is to complete a task a crowd worker:


* Gray, M. L., Suri, S., Ali, S. S., & Kulkarni, D. (2016). [http://sidsuri.com/Publications_files/collab_paper21.pdf The Crowd is a Collaborative Network]. Proceedings of Computer-Supported Cooperative Work. ''[Free Online]''
* '''If you are a US citizen:''' Sign up as a worker on MTurk. Find and complete at least 5 "hits" as a worker on [http://mturk.com Amazon Mechanical Turk]. Note that to do this you will need to create a ''worker'' account on Mturk.
* Kittur et al. (2013). [http://hci.stanford.edu/publications/2013/CrowdWork/futureofcrowdwork-cscw2013.pdf The Future of Crowd Work]. Proceedings of Computer-Supported Cooperative Work. ''[Free Online]''
* '''If you are not a US citizen or if you cannot sign up on MTurk for some other reason:''' Complete at least 3-4 classification tasks in at least 2 different [https://www.zooniverse.org/projects Zooniverse projects] of your choice. Also, complete at least one "study" in [https://www.labinthewild.org/ Lab in the Wild]
* In either case: Record (write down) details and notes about your tasks: What did you do? Who was the requester? What could you was the purpose of the task (as best you could tell)? What was the experience like? What research applications can you (not) imagine for this kind of system?


'''Resources:'''
The second task is to get ready to launch a task as a requestor. We will design and launch tasks in class but I want you to do the following ahead of time:
* [http://www.mturk-tracker.com/ Mturk Tracker]


==== Part II: Discourse Analysis  ====
* Create a "requester" account on [http://mturk.com Amazon Mechnical Turk]. Doing so may require up top 48 hours to be approved so please do that immediately so you have it ready to go in class.
* Put money onto your requestor account to pay workers. A $5 budget should be sufficient for our class. They should take any payment that Amazon does.
* Think of at least one small classification or coding task (e.g., of Tweets, images, etc) and one human subjects data collection tasks like a survey, a survey experiment, etc, that you would like to run. You will have a budget of $5 to run the task!
* If running this task will involve some data (e.g., a set of images or URLs, a set of Tweets, etc), collect that material in a spreadsheet before class. If it will involve a survey, create your survey in a Google Form and/or a Survey Monkey or Qualtrics survey before class.


'''Required Readings:'''
=== Week 6: Saturday February 15: CDSW Session 3 ===


Narrative Analysis:
As description in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the [[Community Data Science Workshops (Winter 2020)]] which I am running concurrently with this class.


* Mitra, A. (1999). [http://doi.org/10.1111/j.1083-6101.1999.tb00330.x Characteristics of the WWW Text: Tracing Discursive Strategies]. Journal of Computer-Mediated Communication, 5(1), 0–0.  ''[Free Online]''
This session will run from 9am-3pm. Details on the [[CDSW Winter 2020]] page.
* Kaun, Anne (2010), "[http://ejournals.library.ualberta.ca/index.php/IJQM/article/view/7165 Open-Ended Online Diaries: Capturing Life as it is Narrated]," International Journal of Qualitative Methods, Vol. 9 Issue 2, p133-148. ''[Free Online]''


Visual Analysis:
=== Week 7: Tuesday February 18: Consulting Week (i.e., no group meeting) ===


* Hochman, N., & Schwartz, R. (2012). [https://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/view/4782 Visualizing Instagram: Tracing Cultural Visual Rhythms]. In Sixth International AAAI Conference on Weblogs and Social Media. ''[Available through UW Libraries]''
During this week, we not meet together. Instead, I will schedule one-on-one in person meetings of an hour with each student individually to catch up with you about your project and to work directly with you to resolve any technical issues you have run into with data collection, etc.
* Hochman, N., & Manovich, L. (2013). [http://firstmonday.org/ojs/index.php/fm/article/viewArticle/4711/ Zooming into an Instagram City: Reading the local through social media]. First Monday, 18(7). ''[Free Online]''


'''Optional Readings:'''
=== Week 8: Tuesday February 25: (I) Discourse Analysis and (II) Visual Analysis ===
 
==== Part I: Discourse Analysis ====
 
'''Required Readings:'''


Narrative Analysis:
* Mitra, Ananda. 1999. “Characteristics of the WWW Text: Tracing Discursive Strategies.” Journal of Computer-Mediated Communication 5 (1): 0–0. https://doi.org/10.1111/j.1083-6101.1999.tb00330.x. {{avail-free|https://doi.org/10.1111/j.1083-6101.1999.tb00330.x}}
* Thurlow, Crispin. 2018. “Digital Discourse: Locating Language in New/Social Media.” In The SAGE Handbook of Social Media, edited by Jean Burgess, Alice Marwick, and Thomas Poell, 135–45. London, UK: SAGE. https://doi.org/10.4135/9781473984066. {{avail-uw|https://doi.org/10.4135/9781473984066}}
* Brock, André. 2018. “Critical Technocultural Discourse Analysis.” New Media & Society 20 (3): 1012–30. https://doi.org/10.1177/1461444816677532. {{avail-uw|https://doi.org/10.1177/1461444816677532}}


*  Gubrium, Aline and K.C. Nat Turner, "[https://canvas.uw.edu/files/36418703/download?download_frd=1 Digital storytelling as an emergent method for social research and practice]," Ch. 21 in HET.
'''Optional Readings:'''


Visual Analysis:
* Kaun, Anne. 2010. “Open-Ended Online Diaries: Capturing Life as It Is Narrated.” International Journal of Qualitative Methods 9 (2): 133–48. https://doi.org/10.1177/160940691000900202. {{avail-uw|https://doi.org/10.1177/160940691000900202}}


* Newbold, Curtis, 2013, "[http://thevisualcommunicationguy.com/2015/01/12/how-to-do-a-visual-analysis-a-five-step-process/ How to Do a Visual Analysis (A 5-Step Process)]". ''[Free Online]''
==== Part II: Visual Analysis ====
: Note: Although I'm not a fan of infograpraphics as a genre, I suppose it makes sense that visual communication people would put together a pretty good one! If you're already familiar with visual analysis from the rhetorical tradition, there's not going to be a lot new here. If this is new for you, this will help you frame and understand the other readings.
* Torralba, A. (2009). [http://videolectures.net/nips09_torralba_uvs/ Understanding Visual Scenes]. Tutorial presented at the NIPS, Vancouver, BC, Canada. Part I. ''[Free Online]''
: Note: This is a two part (each part is one hour) lecture and tutorial by a expert in computer vision. I strongly recommend watching Part I. I think this gives you a good sense of the nature of the kinds of challenges that were (and still are) facing the field of computer vision and anybody trying to have their computer look at images.


These five paper are all technical approaches to doing image classification using datasets from Internet-based datasets of images like Flickr, Google Image Search, Google Street View, or Instagram. Each of these describes interesting and challenges technical issues. If you're interested, it would be a great idea to read these to get a sense for the state of the art and what is and isn't possible:
'''Required Readings:'''


* Jaffe, A., Naaman, M., Tassa, T., & Davis, M. (2006). [http://doi.org/10.1145/1178677.1178692 Generating Summaries and Visualization for Large Collections of Geo-referenced Photographs]. In Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval (pp. 89–98). New York, NY, USA: ACM. ''[Available through UW Libraries]''
* Faulkner, Simon, Farida Vis, and Francesco D’Orazio. 2018. “Analysing Social Media Images.” In The SAGE Handbook of Social Media, edited by Jean Burgess, Alice Marwick, and Thomas Poell, 160–78. London, UK: SAGE. https://doi.org/10.4135/9781473984066. {{avail-uw|https://doi.org/10.4135/9781473984066}}
* Simon, I., Snavely, N., & Seitz, S. M. (2007). [http://doi.org/10.1109/ICCV.2007.4408863 Scene Summarization for Online Image Collections]. In Computer Vision, IEEE International Conference on (Vol. 0, pp. 1–8). Los Alamitos, CA, USA: IEEE Computer Society. ''[Free Online]''
* Casas, Andreu, and Nora Webb Williams. 2019. “Images That Matter: Online Protests and the Mobilizing Role of Pictures.” Political Research Quarterly 72 (2): 360–75. https://doi.org/10.1177/1065912918786805. {{avail-uw|https://doi.org/10.1177/1065912918786805}}
* Crandall, D. J., Backstrom, L., Huttenlocher, D., & Kleinberg, J. (2009). [http://doi.org/10.1145/1526709.1526812 Mapping the World’s Photos]. In Proceedings of the 18th International Conference on World Wide Web (pp. 761–770). New York, NY, USA: ACM. ''[Available through UW Libraries]''
* Casas, Andreu, and Nora Webb Williams. 2017. “Computer Vision for Political Science Research: A Study of Online Protest Images.” In. College Park, PA: Pennsylvania State University. http://andreucasas.com/casas_webb_williams_NewFaces2017_images_as_data.pdf. {{avail-free|http://andreucasas.com/casas_webb_williams_NewFaces2017_images_as_data.pdf}}
* San Pedro, J., & Siersdorfer, S. (2009). [http://doi.org/10.1145/1526709.1526813 Ranking and Classifying Attractiveness of Photos in Folksonomies]. In Proceedings of the 18th International Conference on World Wide Web (pp. 771–780). New York, NY, USA: ACM. ''[Available through UW Libraries]''
* Hochman, Nadav, and Raz Schwartz. 2012. “Visualizing Instagram: Tracing Cultural Visual Rhythms.In Sixth International AAAI Conference on Weblogs and Social Media. https://pdfs.semanticscholar.org/780d/c7ff86eb36731d5faa043ac635cbae6bbe45.pdf. {{avail-free|https://pdfs.semanticscholar.org/780d/c7ff86eb36731d5faa043ac635cbae6bbe45.pdf}}
* Doersch, C., Singh, S., Gupta, A., Sivic, J., & Efros, A. A. (2012). [http://doi.org/10.1145/2185520.2185597 What Makes Paris Look Like Paris?] ACM Trans. Graph., 31(4), 101:1–101:9. ''[Available through UW Libraries]''


Discourse Analysis:
'''Optional Readings:'''


* Honeycutt, Courtenay (2005), “[http://onlinelibrary.wiley.com/enhanced/doi/10.1111/j.1083-6101.2005.tb00240.x Hazing as a process of boundary maintenance in an online community]”, Journal of Computer-Mediated Communication, 10(2). [Available through UW Libraries]
* Torralba, Antonio. 2009. “Understanding Visual Scenes.” Tutorial presented at the NIPS, Vancouver, BC, Canada. http://videolectures.net/nips09_torralba_uvs/. {{avail-uw|http://videolectures.net/nips09_torralba_uvs/}}
:Note: Combines quantitative and qualitative computer-mediated discourse analysis methods.*
: Note: This is a two-part (each part is one hour) lecture and tutorial by an expert in computer vision. I strongly recommend watching Part I. I think this gives you a good sense of the nature of the kinds of challenges that were (and still are) facing the field of computer vision and anybody trying to have their computer look at images.
* Hochman, Nadav, and Lev Manovich. 2013. “Zooming into an Instagram City: Reading the Local through Social Media.” First Monday 18 (7). https://firstmonday.org/article/view/4711/3698. {{avail-free|https://firstmonday.org/article/view/4711/3698}}


=== Week 6: Saturday February 15: CDSW Session 3 ===
These five papers are all technical approaches to doing image classification using datasets from Internet-based datasets of images like Flickr, Google Image Search, Google Street View, or Instagram. Each of these describes interesting and challenges technical issues. If you're interested, it would be a great idea to read these to get a sense for the state of the art and what is and isn't possible:


As description in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the [[Community Data Science Workshops (Winter 2020)]] which I am running concurrently with this class.
* Jaffe, Alexandar, Mor Naaman, Tamir Tassa, and Marc Davis. 2006. “Generating Summaries and Visualization for Large Collections of Geo-Referenced Photographs.” In Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval, 89–98. MIR ’06. New York, NY, USA: ACM. https://doi.org/10.1145/1178677.1178692. {{avail-uw|https://doi.org/10.1145/1178677.1178692}}
* Simon, Ian, Noah Snavely, and Steven M. Seitz. 2007. “Scene Summarization for Online Image Collections.” In Computer Vision, IEEE International Conference On, 0:1–8. Los Alamitos, CA, USA: IEEE Computer Society. https://doi.org/10.1109/ICCV.2007.4408863. {{avail-free|https://doi.org/10.1109/ICCV.2007.4408863}}
* Crandall, David J., Lars Backstrom, Daniel Huttenlocher, and Jon Kleinberg. 2009. “Mapping the World’s Photos.” In Proceedings of the 18th International Conference on World Wide Web, 761–770. WWW ’09. New York, NY, USA: ACM. https://doi.org/10.1145/1526709.1526812. {{avail-uw|https://doi.org/10.1145/1526709.1526812}}
* San Pedro, Jose, and Stefan Siersdorfer. 2009. “Ranking and Classifying Attractiveness of Photos in Folksonomies.” In Proceedings of the 18th International Conference on World Wide Web, 771–780. WWW ’09. New York, NY, USA: ACM. https://doi.org/10.1145/1526709.1526813. {{avail-uw|https://doi.org/10.1145/1526709.1526813}}
* Doersch, Carl, Saurabh Singh, Abhinav Gupta, Josef Sivic, and Alexei A. Efros. 2012. “What Makes Paris Look like Paris?” ACM Trans. Graph. 31 (4): 101:1–101:9. https://doi.org/10.1145/2185520.2185597. {{avail-uw|https://doi.org/10.1145/2185520.2185597}}


This session will run from 9am-3pm. Details on the [[CDSW Winter 2020]] page.
=== Week 9: Tuesday March 3: Consulting Week ===


=== Week 7: Tuesday February 18: Consulting Week (i.e., no group meeting) ===
During this week, we will not meet together. Instead, I will schedule one-on-one in-person meetings of an hour with each student individually to catch up with you about your project and to work directly with you to resolve any technical issues you have run into with data collected.


During this week, we not meet together. Instead, I will schedule one-on-one in person meetings of an hour with each student individually to catch up with you about your project and to work directly with you to resolve any technical issues you have run into with data collection, etc.
=== Week 10: Tuesday March 10: Final Presentations  ===


=== Week 8: Tuesday February 25: Consulting Week (i.e., no group meeting) ===
<!--


During this week, we not meet together. Instead, I will schedule one-on-one in person meetings of an hour with each student individually to catch up with you about your project and to work directly with you to resolve any technical issues you have run into with data collect


=== Week 9: Tuesday March 3: (I) Design Research and (II) Digital Trace and Sensor Data ===
==== Part I: Design Research ====
==== Part I: Design Research ====
Today we'll have a guest visitor — [http://www.andresmh.com/ Andrés Monroy-Hernández] who is director of HCI research at SNAP and formerly from [http://fuse.microsoft.com/ Microsoft Resarch's FUSE labs]. Andrés is affiliate faculty in the Department of Communication and Department of Human-Centered Design and Engineering at UW. Monroy-Hernández research involves studying people by designing and building systems. He's built a number of very large and successful socio-technical systems as part of his research. In his graduate work, he build the [http://scratch.mit.edu/ Scratch Online Community] which is now used by more than 10 million people.
Today we'll have a guest visitor — [http://www.andresmh.com/ Andrés Monroy-Hernández] who is director of HCI research at SNAP and formerly from [http://fuse.microsoft.com/ Microsoft Research's FUSE labs]. Andrés is affiliate faculty in the Department of Communication and Department of Human-Centered Design and Engineering at UW. Monroy-Hernández's research involves studying people by designing and building systems. He's built a number of very large and successful socio-technical systems as part of his research. In his graduate work, he build the [http://scratch.mit.edu/ Scratch Online Community] which is now used by more than 10 million people.


I've asked him to come and talk to us about design research as a process. As a result, it will be helpful to read about two projects he has worked on recently that he will talked to us about. Those projects are called NewsPad and Eventful.
I've asked him to come and talk to us about design research as a process. As a result, it will be helpful to read about two projects he has worked on recently that he will talked to us about. Those projects are called NewsPad and Eventful.
Line 560: Line 586:


* Eagle, Nathan, "[https://canvas.uw.edu/files/36870285/download?download_frd=1 Mobile phones as sensors for social research]," Ch. 22 in HET.
* Eagle, Nathan, "[https://canvas.uw.edu/files/36870285/download?download_frd=1 Mobile phones as sensors for social research]," Ch. 22 in HET.
* Visser, Albertine and Ingrid Mulder, "[https://canvas.uw.edu/files/36870283/download?download_frd=1 Emergent technologies for assessing social feelings and experiences]," Ch. 16 in HET.
* Visser, Albertine, and Ingrid Mulder, "[https://canvas.uw.edu/files/36870283/download?download_frd=1 Emergent technologies for assessing social feelings and experiences]," Ch. 16 in HET.
* de Haan, Geert, et. al., "[https://canvas.uw.edu/files/36870284/download?download_frd=1 Bringing the research lab into everyday life: Exploiting sensitive environments to acquire data for social research]," Ch. 23 in HET.
* de Haan, Geert, et. al., "[https://canvas.uw.edu/files/36870284/download?download_frd=1 Bringing the research lab into everyday life: Exploiting sensitive environments to acquire data for social research]," Ch. 23 in HET.
* Fowler, Chris, et. al., "[https://canvas.uw.edu/files/36870282/download?download_frd=1 Living laboratories: Social research applications and evaluations]," Ch. 27 in HET.
* Fowler, Chris, et. al., "[https://canvas.uw.edu/files/36870282/download?download_frd=1 Living laboratories: Social research applications and evaluations]," Ch. 27 in HET.
* Holohan, Anne, et. al., "[https://canvas.uw.edu/files/36870280/download?download_frd=1 The digital home: A new locus of social science research]," Ch. 28 in HET.
* Holohan, Anne, et. al., "[https://canvas.uw.edu/files/36870280/download?download_frd=1 The digital home: A new locus of social science research]," Ch. 28 in HET.


=== Week 10: Tuesday March 10: Final Presentations  ===
 
-->


== Administrative Notes ==
== Administrative Notes ==
=== Your Presence in Class ===
=== Your Presence in Class ===


As detailed in [[#Participation|the section on participation]] and in [[Teaching Assessment|my page on assessment]], class participation is a critical way that I will assess learning in the class. Obviously, you must be in class in order to participate. If you need to miss class for any reason, please contact me ahead of time (email is best). In the event of an absence, you are responsible for obtaining class notes, handouts, assignments, etc.
As detailed in [[#Participation|the section on participation]] and in [[User:Benjamin Mako Hill/Assessment|my page on assessment]], class participation is a critical way that I will assess learning in the class. Obviously, you must be in class in order to participate. If you need to miss class for any reason, please contact me ahead of time (email is best). In the event of an absence, you are responsible for obtaining class notes, handouts, assignments, etc.


=== Office Hours ===
=== Office Hours ===


I will hold office Hours on '''Thursdays 1-2pm''' in [https://uw.edu/maps/?cmu Communications (CMU) 333]. In addition to my scheduled office hours, I am generally in [[Community Data Science Lab (UW)|my lab in CMU 306]]. Feel free to stop by at any time or to contact me to arrange a time to meet.
I will hold office hours on '''Thursdays 1-2 pm ''' in [https://uw.edu/maps/?cmu Communications (CMU) 333]. In addition to my scheduled office hours, I am generally in [[Community Data Science Lab (UW)|my lab in CMU 306]]. Feel free to stop by at any time or to contact me to arrange a time to meet.


=== Religious Accommodations ===
=== Religious Accommodations ===


Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at [https://registrar.washington.edu/staffandfaculty/religious-accommodations-policy/ Religious Accommodations Policy]. Accommodations must be requested within the first two weeks of this course using the [https://registrar.washington.edu/students/religious-accommodations-request/ Religious Accommodations Request form].
Washington state law requires that UW develop a policy for the accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at [https://registrar.washington.edu/staffandfaculty/religious-accommodations-policy/ Religious Accommodations Policy]. Accommodations must be requested within the first two weeks of this course using the [https://registrar.washington.edu/students/religious-accommodations-request/ Religious Accommodations Request form].


=== Student Conduct ===
=== Student Conduct ===
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Safety
Safety


Call SafeCampus at 206-685-7233 anytime–no matter where you work or study–to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested.
Call SafeCampus at 206-685-7233 anytime–no matter where you work or study–to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support while discussing short- and long-term solutions and connecting you with additional resources when requested.


=== Academic Dishonesty ===
=== Academic Dishonesty ===
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=== Disability Resources ===
=== Disability Resources ===


If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to uw at your earliest convenience so we can discuss your needs in this course.
If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to UW at your earliest convenience so we can discuss your needs in this course.


If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or uwdrs@uw.edu or disability.uw.edu. DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.
If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or uwdrs@uw.edu or disability.uw.edu. DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.
Line 603: Line 630:
== Credit and Notes ==
== Credit and Notes ==


This will be third time I have taught this course at UW in its current form. This syllabuses draws heavily from previous versions. Syllabuses from earlier classes can be found online at:
This will be the third time I have taught this course at UW in its current form. This syllabus draws heavily from previous versions. Syllabuses from earlier classes can be found online at:


* [[Internet Research Methods (Spring 2016)]]
* [[Internet Research Methods (Spring 2016)]]
* [https://mako.cc/teaching/2015/internet_research/ Internet Research Methods (Spring 2015)]
* [https://mako.cc/teaching/2015/internet_research/ Internet Research Methods (Spring 2015)]


This syllabus was inspired by, and borrows with permission from, a syallbus from an earlier version of this class taught by [http://www.com.washington.edu/foot/ Kirsten Foot]. Professor Foot last taught the course in Spring 2014.
This syllabus was inspired by and borrows with permission from, a syllabus from an earlier version of this class taught by [http://www.com.washington.edu/foot/ Kirsten Foot]. Professor Foot last taught the course in Spring 2014.

Latest revision as of 21:56, 26 March 2022

Designing Internet Research
COM528 - Department of Communication, University of Washington
Instructor: Benjamin Mako Hill (University of Washington)
Course Websites:
Course Catalog Description:
Focuses on designing Internet research, assessing the adaptation of proven methods to Internet tools and environments, and developing new methods in view of particular capacities and characteristics of Internet applications. Legal and ethical aspects of Internet research receive ongoing consideration.

Overview and Learning Objectives[edit]

What new lines of inquiry and approaches to social research are made possible and necessary by the Internet? In what ways have established research methods been affected by the Internet? How does the Internet challenge established methods of social research? How are researchers responding to these challenges?

These are some of the key questions we will explore in this course. The course will focus on assessing the incorporation of Internet tools in established and emergent methods of social research, the adaptation of social research methods to study online phenomena, and the development of new methods and tools that correspond with the particular capacities and characteristics of the Internet. The readings will include both descriptions of Internet-related research methods with an eye to introducing skills and examples of studies that use them. The legal and ethical aspects of Internet research will receive ongoing consideration throughout the course. The purpose of this course is to help prepare students to design high quality research projects that use the Internet to study online communicative, social, cultural, and political phenomena.

I will consider the course a complete success if every student is able to do all of these things at the end of the quarter:

  • Discuss and compare distinct types of Internet research including: web archiving; textual analysis; ethnography; interviews; network analyses of social and hyperlink networks; analysis of digital trace data, traditional, natural, and field experiments; design research; interviewing; survey research; and narrative and visual analyses.
  • Describe particular challenges and threats to research validity associated with each method.
  • For at least one method, be able to provide a detailed description of a research project and feel comfortable embarking on a formative study using this methodology.
  • Given a manuscript (e.g., in the context of a request for peer review), be able to evaluate an Internet-based study in terms of its use its methodological choices.
  • Use a modern programming language (like Python) to collect a dataset from a web API like those published by Twitter, Reddit, or Wikipedia.

Note About This Syllabus[edit]

You should expect this syllabus to be a dynamic document. Although the core expectations for this class are fixed, the details of readings and assignments will shift based on how the class goes, guest speakers that I arrange, my own readings in this area, etc. As a result, there are three important things to keep in mind:

  • Although details on this syllabus will change, I will try to ensure that I never change readings more than six days before they are due. I will send an announcement no later than before each Wednesday evening that fixes the schedule for the next week. This means that if I don't fill in a reading marked "[To Be Decided]" six days before it's due, it is dropped. If we don't change something marked "[Tentative]" before the deadline, then it is assigned. This means that if you plan to read more than six days ahead, contact the teaching team first.
  • Because this syllabus a wiki, you will be able to track every change by clicking the history button on this page when I make changes. I will summarize these changes in the weekly an announcement on Canvas sent that will be emailed to everybody in the class. Closely monitor your email or the announcements section on the course website on Canvas to make sure you don't miss these!
  • I will ask the class for voluntary anonymous feedback frequently — especially toward the beginning of the quarter. Please let me know what is working and what can be improved. In the past, I have made many adjustments to courses that I teach while the quarter progressed based on this feedback.

Books[edit]

This class has no textbook and I am not requiring you to buy any books for this class. That said, several required readings and many suggested readings, will come from several excellent books which you might want to consider adding to your library:

These books include:

  • Burgess, Jean, Alice Marwick, and Thomas Poell, eds. 2018. The SAGE Handbook of Social Media. London, UK: SAGE. [Available through UW libraries]
  • Foucault Welles, Brooke, and Sandra González-Bailón, eds. 2018. The Oxford Handbook of Networked Communication. London, UK: Oxford University Press. [Available through UW libraries]
  • Hargittai, Eszter, and Christian Sandvig, eds. 2015. Digital Research Confidential: The Secrets of Studying Behavior Online. MIT Press. [Available through UW libraries
  • Hesse-Biber, Sharlene Nagy, ed. 2011. The Handbook of Emergent Technologies in Social Research. Oxford, UK: Oxford University Press.
  • Hewson, Claire, Carl Vogel, and Dianna Laurent. 2016. Internet Research Methods. London, UK: SAGE. https://doi.org/10.4135/9781473920804. [Available through UW libraries]
  • Snee, Helene, Christine Hine, Yvette Morey, Steven Roberts, and Hayley Watson, eds. 2016. Digital Methods for Social Science: An Interdisciplinary Guide to Research Innovation. New York, NY: Palgrave-Macmillan. [Available through UW libraries]

Technical Skills[edit]

Nearly all of our structured in-person meetings and all of our readings will focus on teaching conceptual skills related to Internet research. These skills involve the "softer" skills of understanding, designing, and critiquing research plans. These are harder to teach, evaluate, and learn but are ultimately what will make a research project interesting, useful, or valid. When the course has been taught in the past by other faculty, it has been entirely focused on these types of conceptual skills.

That said, I also believe that any skilled Internet researcher must be comfortable writing code to collect a dataset from the web or, at the very least, should have enough experience doing so that they know what is involved and what is possible and impossible. This is essential even if your only goals is to manage somebody else writing code and gathering data or work productively with a collaborator who is doing so. As a result, being successful in this class will also require technical skills.

Because students are going to come to the class with different technical skillsets, we well be devoting a relatively small chunk of class time to developing technical skills. Instead, I'm requiring that students build these skills outside of our meetings together if they do not have them already.

In particular, I want every student to have the following three things:

  1. Basic skills in a general purpose high-level programming language used for Internet-based data collection and analysis. I strongly recommend the Python programming language although other programming languages like Ruby and Perl are also good choices. Generally speaking, statistical programming languages like R, Stata, Matlab are not well suited for this.
  2. Familiarity with the technologies of web APIs. In particular, students should understand what APIs are, how they work, and should be able to read, interpret, and process data in JSON.
  3. Knowledge of how to process and move data from a website or API into a format that they will be able to use for analysis. The final format will depend on the nature of the result but this might be a statistical programming environment like R, Stata, SAS, SPSS, etc or a qualitative data analysis tools like ATLAS.ti, NVivo or Dedoose.

If you are already comfortable doing these things, great.

If you are not yet comfortable, I am going to be organizing three free workshops called the Community Data Science Workshops on Saturdays in April and May and I extremely strongly recommend that you attend them. The workshops will teach exactly the skills I'm expecting you to have and attending the full series of workshops will be enough to fulfill this requirement.

The workshops will meet four times so please block these out on your calendar now:

  1. Friday January 17 6-9pm
  2. Saturday January 18 9:45am-4pm
  3. Saturday February 1 9:45am-4pm
  4. Saturday February 15 9:45am-4pm

I've offered this workshops four times previously and they have always been oversubscribed. As a result, you should register for these workshops immediately. You can find the registration link on this page. Please mention that you are in this class when you register so that we make sure that you accept your application.

I have taught these workshops five times before in 2014, 2015, and 2016. If you have taken them in the past, you do not need to take them again. If you took them before but are feeling unsure about your skills, you will be welcome to come back to review and brush up on the material.

If you do not have the technical skills required above and you will not attend the workshops, you're going to be responsible for learning this material on your own. Although this is totally fine, I suspect it present a major challenge to success in this class. If you will be in this situation, contact me before the quarter starts.

Assignments[edit]

The assignments in this class are designed to give you an opportunity to try your hand at using the conceptual material taught in the class. There will be no exams or quizzes. Unless otherwise noted, all assignments are due at the end of the day (i.e., 11:59pm on the day they are due).

Weekly Reflections[edit]

Deliverables
(1) Post a message in the appropriate course discussion board; (2) Respond to at least one of your classmates before class.
Due Date
(1) Every Monday (on a week with reading); (2) Every Tuesday at 1:30 (on a week with reading)
Maximum length
1,000 words

For every week that we have readings (i.e., every week except for the consulting weeks and and the final presentation weeks), I'm asking everybody to reflect on the readings by the day before class and to share their reflections with everybody else. Because we're skipping the first week, that works out to a total of six reflections.

Reflections should be no more than 1000 words (about one single-spaced page). So everyone will have a chance to read the reflections before class, response papers should be posted to our course website the day before (i.e., before midnight each Monday) so that we can all read and construct responses. Please also pose one or two open-ended discussion questions that may serve as jumping off points for our in-class conversation. Don't bother with summarizing (we've all done the reading after all) and focus on engaging with ideas.

In terms of content, response papers offer you an opportunity to engage the readings by identifying common or conflicting premises, thinking through potential implications, offering political or cultural examples, posing well-supported objections, or outlining critical extensions. In my experience, the most thought provoking reflections go beyond pointing out things that one wonders about or finds interesting and explain why you find it interesting.

Turn in your response paper to Canvas by posting a new message in the appropriate day in the course the discussion board.

I'd also like everybody read over everybody else's responses and respond to at least one person—evening things out so that not everybody response to one person would be nice, but use your judgement.

Research Project[edit]

As a demonstration of your learning in this course, you will design a plan for an internet research project and will, if possible, also collect (at least) an initial sample of a dataset that you will use to complete the project.

The genre of the paper you can produce can take one of the following three forms:

  1. A draft of a manuscript for submission to a conference or journal.
  2. A proposal for funding (e.g., for submission for the NSF for a graduate student fellowship).
  3. A draft of the methods chapter of your dissertation.

In any the three paths, I expect you take this opportunity to produce a document that will further your to academic career outside of the class.

Project Identification[edit]

Due Date
January 24
Maximum paper length
800 words (~3 pages)
Deliverables
Turn in [in the appropriate Canvas dropbox]

Early on, I want you to identify your final project. Your proposal should be short and can be either paragraphs or bullets. It should include the following things:

  • The genre of the project and a short description of how it fits into your career trajectory.
  • A one paragraph abstract of the proposed study and research question, theory, community, and/or groups you plan to study.
  • A short description of the type of data you plan to collect as part of your final project.

Final Project[edit]

Outline Due Date
February 23
Maximum outline length
2 pages
Presentation Date
March 10
Paper Due Date
March 20
Maximum outline length
8000 words (~27 pages)
All Deliverables
Turn in in the appropriate Canvas dropboxes

Because the emphasis in this class is on methods and because I'm not an expert in each of your areas or fields, I'm happy to assume that your paper, proposal, or thesis chapter has already established the relevance and significance of your study and has a comprehensive literature review, well-grounded conceptual approach, and compelling reason why this research is so important. Instead of providing all of this details, instead feel free to start with a brief summary of the purpose and importance of this research, and an introduction of your research questions or hypotheses. If your provide more detail, that's fine, but I won't give you detailed feedback on this parts.

The final paper should include:

  • a statement of the purpose, central focus, relevance and significance of this research;
  • a description of the specific Internet application(s) and/or environment(s) and/or objects to be studied and employed in the research;
  • key research questions or hypotheses;
  • operationalization of key concepts;
  • a description and rationale of the specific method(s), (if more than one method will be used, explain how the methods will produce complementary findings);
  • a description of the step-by-step plan for data collection;
  • description and rationale of the level(s), unit(s) and process of analysis (if more than one kind of data are generated, explain how each kind will be analyzed individually and/or comparatively);
  • an explanation of how these analyses will enable you to answer the RQs
  • a sample instrument (as appropriate);
  • a sample dataset and description of a formative analysis you have completed;
  • a description of actual or anticipated results and any potential problems with their interpretation;
  • a plan for publishing/disseminating the findings from this research
  • a summary of technical, ethical, human subjects and legal issues that may be encountered in this research, and how you will address them;
  • a schedule (using specific dates) and proposed budget.

I also expect each student to begin data collection for your project (i.e., using the technical skills you learn in the class) and describe your progress in this regard this in your paper. If collecting data for a proposed project is impractical (e.g., because of IRB applications, funding, etc) I would love for you to engage in the collection of public dataset as part of a pilot or formative study. If this is not feasible or useful, we can discuss other options.

I have a strong preference for you to write this paper individually but I'm open to the idea that you may want to work with others in the class.

Participation[edit]

The course relies heavily on participation and discussion. It is important to realize that we will not summarize reading in class and I will not cover it in lecture. I expect you all to have read it and we will jump in and start discussing it. The "Participation Rubric" section of my detailed page on assessment gives the rubric I will use in evaluating participation.

Assessment[edit]

I have put together a very detailed page that describes the way I approach assessment and grading—both in general and in this course. Please read it carefully I will assign grades for each of following items on the UW 4.0 grade scale according to the weights below:

  • Participation: 30%
  • Weekly Reflection: 15%
  • Proposal identification: 5%
  • Final paper outline: 5%
  • Final Presentation: 10%
  • Final Paper: 35%

Schedule[edit]

Week 1: Tuesday January 7: (I) Introduction and (II) Ethics[edit]

Part I: Introduction and Framing[edit]

Required Readings:

Optional Reading:

  • December, John. 1996. “Units of Analysis for Internet Communication.” Journal of Computer-Mediated Communication 1 (4): 0–0. https://doi.org/10.1111/j.1083-6101.1996.tb00173.x. [Available free online]
  • Sandvig, Christian, and Eszter Hargittai. 2015. “How to Think about Digital Research.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig, 1–28. Cambridge, MA: MIT Press. [Available in Canvas]

Part II: Ethics[edit]

Required Readings:

To frame a conversation around research ethics, lets read this piece:

And these pieces that are all vaguely in response to it:

Optional Readings:

  • Department of Health, Education, and Welfare, and National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. 2014. “The Belmont Report. Ethical Principles and Guidelines for the Protection of Human Subjects of Research.” http://www.hhs.gov/ohrp/policy/belmont.html. [Available free online]
  • Frankel, Mark S., and Sanyin Siang. 1999. “Ethical and Legal Aspects of Human Subject Research on the Internet.” Workshop Report. Washington, DC: American Association for the Advancement of Science. [Available free online]

Week 2: Tuesday January 14: (I) Internet Data Collection (II) Textual Analysis[edit]

Part I: Internet Data Collection[edit]

Required Readings:

Optional Readings:

  • Ankerson, Megan Sapnar. 2015. “Read/Write the Digital Archive: Strategies for Historical Web Research.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig, 29–54. Cambridge, MA: MIT Press. [Available in Canvas]
  • Spaniol, Marc, Dimitar Denev, Arturas Mazeika, Gerhard Weikum, and Pierre Senellart. 2009. “Data Quality in Web Archiving.” In Proceedings of the 3rd Workshop on Information Credibility on the Web, 19–26. WICOW ’09. New York, NY, USA: ACM. https://doi.org/10.1145/1526993.1526999. [Available through UW Libraries]
  • Schneider, Steven M., and Kirsten A. Foot. 2004. “The Web as an Object of Study.” New Media & Society 6 (1): 114–22. https://doi.org/10.1177/1461444804039912. [Available through UW Libraries]
  • Weber, Matthew S. 2014. “Observing the Web by Understanding the Past: Archival Internet Research.” In Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, 1031–1036. WWW Companion ’14. Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/2567948.2579213. [Available through UW Libraries]

Optional readings related to the ethics of data collection online:

Two useful sources of data collection:

  • Archive Team is an online community that archives websites. They are a fantastic resource and include many pieces of detailed technical documentation on the practice of engaging in web archiving. For example, here are detailed explanations of mirroring a website with GNU wget which is the piece of free software I usually use to archive websites.
  • OpenHumans is an online community where people share personal data with each other and with researchers.

Part II: Textual Analyses[edit]

Required Readings:

Optional Readings:

I'm assuming you have at least a rough familiarity with content analysis as a methodology. If your not as comfortable with this, check out the Wikipedia article to start. These help provide more of a background into content analysis (in general, and online):

  • Van Selm, Martine & Jankowski, Nick, (2005) "Content Analysis of Internet-Based Documents." Unpublished Manuscript. [Available in Canvas]
  • Neuendorf, K. A. (2002). The content analysis guidebook. Thousand Oaks, Calif.: Sage Publications. [Available from Instructor]
  • Krippendorff, K. (2005). Content analysis: an introduction to its methodology. Thousand Oaks; London; New Delhi: Sage. [Available from Instructor]

Examples of more traditional content analysis using online content:

Another example of topic modeling from political science:

Week 2: Friday January 17: CDSW Session 0[edit]

As description in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the Community Data Science Workshops (Winter 2020) which I am running concurrently with this class.

This session will run from 6-9pm and is the only session which can probably be missed. Please do contact me, however, if you will not be able to attend it.

Week 2: Saturday January 18: CDSW Session 1[edit]

As description in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the Community Data Science Workshops (Winter 2020) which I am running concurrently with this class.

This session will run from 9am-3pm. Details on the CDSW Winter 2020 page.

Week 3: Tuesday January 21: (I) Network Analysis and (II) Hyperlink Networks[edit]

Part I: Network Analysis[edit]

Required Readings:

Optional Readings:

Network datasets:

Part II: Hyperlink Networks[edit]

Optional readings:

Tools for collecting hyperlink network data:

  • Issue Crawler — network mapping software by the Govcom.org Foundation, Amsterdam in a group run by Richard Rogers
  • Virtual Observatory for the Study of Online Networks (VOSON) — "web-based software incorporating web mining, data visualisation, and traditional empirical social science methods (e.g. social network analysis, SNA). Text analysis, dataset manipulation and visualisation, and social network analysis (SNA) are available within an integrated environment."

Week 4: Tuesday January 28: (I) Ethnography and (II) Interviews[edit]

Part I: Digital & Trace Ethnography[edit]

Required Readings:

More traditional ethnographic research in online settings:

  • Hines, Christine. 2017. “Ethnographies of Online Communities and Social Media: Modes, Varieties, Affordances.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 401–15. London, UK: SAGE. [Available in Canvas]
  • [Selections] Jemielniak, Dariusz. 2014. Common Knowledge?: An Ethnography of Wikipedia. Stanford, California: Stanford University Press. ["Introduction" and "Appendix A: Methodology"; Available in Canvas]

Material on "Trace" and "network" ethnographies:

Optional Readings:

  • Hine, Christine. 2000. Virtual Ethnography. London, UK: SAGE Publications. [Available from the Instructor]
This is the canonical book-length account and the main citation in this space.
Note: You may also be interest in reading the essay by Hine that boyd is responding to. [Available in Canvas]
  • Hjorth, Larissa, Heather Horst, Anne Galloway, and Genevieve Bell, eds. 2016. The Routledge Companion to Digital Ethnography. New York, NY: Routledge. [Available from the instructor]
  • Sinanan, Jolynna, and Tom McDonald. 2018. “Ethnography.” In The SAGE Handbook of Social Media, 179–95. 55 City Road: SAGE Publications Ltd. https://doi.org/10.4135/9781473984066. [Available through UW libraries]
  • Maxwell, Joseph A. 2002. “Understanding and Validity in Qualitative Research.” In The Qualitative Researcher’s Companion, edited by A. M. Huberman and Matthew B. Miles, 37–64. London, UK: SAGE. [Available in Canvas]
  • Champion, Kaylea, Nora McDonald, Stephanie Bankes, Joseph Zhang, Rachel Greenstadt, Andrea Forte, and Benjamin Mako Hill. 2019. “A Forensic Qualitative Analysis of Contributions to Wikipedia from Anonymity Seeking Users.” Proceedings of the ACM on Human-Computer Interaction 3 (CSCW): 53:1–53:26. https://doi.org/10.1145/3359155. [Available through UW libraries]

These are all other interesting and/or frequently cited examples of Internet-based ethnographies:

Note: To conduct the study reported in this paper the authors created a used a fake profile in order to observe the psychological support offered to participants.
Note: Fantastic more general introduction but takeaways that are more specifically targeted toward people studying virtual reality type environments with virtual physicality.

Charlie's optional readings (virtual world ethnographies):

  • Bainbridge, William Sims. 2010. The Warcraft Civilization: Social Science in a Virtual World. Cambridge, Massachusetts: MIT. [mitpress https://mitpress.mit.edu/books/warcraft-civilization]
  • Nardi, Bonnie A. 2009. My Life as a Night Elf Priest: An Anthropological Account of World of Warcraft. Ann Arbor, Michigan: University of Michigan. [free pdfs https://muse.jhu.edu/book/1093]
  • Pearce, Celia, Tom Boellstorff, and Bonnie A. Nardi. 2011. Communities of Play: Emergent Cultures in Multiplayer Games and Virtual Worlds. The MIT Press. [mitpress https://mitpress.mit.edu/books/communities-play]
  • Boellstorff, Tom, Bonnie Nardi, Celia Pearce, T. L. Taylor, and George E. Marcus. 2012. Ethnography and Virtual Worlds: A Handbook of Method. Princeton: Princeton University Press. [1]

Part II: Online Interviewing[edit]

Required Readings:

  • O’Connor, Henrietta, and Clare Madge. 2017. “Internet-Based Interviewing.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 416–34. London, UK: SAGE. [Available through Canvas]
  • Abrams, Katie M ., and Ted J. Gaiser. 2017. “Online Focus Groups.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 435–50. London, UK: SAGE. [Available through Canvas]
  • Hanna, Paul. 2012. “Using Internet Technologies (Such as Skype) as a Research Medium: A Research Note.” Qualitative Research 12 (2): 239–42. https://doi.org/10.1177/1468794111426607. [Available through UW libraries]
Note: Short article you can basically skim. Read it quickly so you can cite it later.

Optional Readings:

  • boyd, danah. 2015. “Making Sense of Teen Life: Strategies for Capturing Ethnographic Data in a Networked Era.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig. Cambridge, Massachusetts: MIT Press. [Available in Canvas]
Note: Strongly focused on ethnographic interviews with tons of very specific details. Fantastic article on interviewing, although perhaps a bit weak on Internet-specific advice.
  • Markham, Annette N. 1998. “The Shifting Project, The Shifting Self.” In Life Online: Researching Real Experience in Virtual Space, 61–83. Rowman Altamira. [Available from instructor]
Note: One of the earliest books on online life and one of the earliest attempts to do online interviewing. This is dated, but highlight some important challenge.

Alternate Accounts:

These texts are largely redundant to the required texts above but do provide a different perspective and examples:

  • Salmons, Janet. 2014. Qualitative Online Interviews: Strategies, Design, and Skills. SAGE Publications. [Preface, TOC, and Chapter 1; Available in Canvas]
This is a book that lays out what claims to be a comprehensive account to online interviewing. I have the book and am happy to loan my copy to anybody in the class that thinks this will be a core part of their research.

Optional readings related to the ethics of identify subjects:

Week 4: Saturday February 1: CDSW Session 2[edit]

As described in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the Community Data Science Workshops (Winter 2020) which I am running concurrently with this class.

This session will run from 10 am-4 pm. Details on the CDSW Winter 2020 page.

Week 5: Tuesday February 4: (I) Surveys and (II) Experiments[edit]

Part I: Surveys[edit]

Required Readings:

  • Fricker, Jr., Ronald D., and Katja Lozar Manfreda. 2017. “Sampling Methods for Online Surveys.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 162–83. London, UK: SAGE. [Available in Canvas]
  • Walejko, Gina. 2009. “Online Survey: Instant Publication, Instant Mistake, All of the Above.” In Research Confidential: Solutions to Problems Most Social Scientists Pretend They Never Have, edited by Eszter Hargittai, 101–21. Ann Arbor, MI: University of Michigan Press. [Available in Canvas]
  • Konstan, Joseph A., B. R. Simon Rosser, Michael W. Ross, Jeffrey Stanton, and Weston M. Edwards. 2005. “The Story of Subject Naught: A Cautionary but Optimistic Tale of Internet Survey Research.” Journal of Computer-Mediated Communication 10 (2): 00–00. https://doi.org/10.1111/j.1083-6101.2005.tb00248.x. [Free online]
  • Hill, Benjamin Mako, and Aaron Shaw. 2013. “The Wikipedia Gender Gap Revisited: Characterizing Survey Response Bias with Propensity Score Estimation.” PLoS ONE 8 (6): e65782. https://doi.org/10.1371/journal.pone.0065782. [Free online]
  • Salganik, Matthew J., and Karen E. C. Levy. 2015. “Wiki Surveys: Open and Quantifiable Social Data Collection.” PLOS ONE 10 (5): e0123483. https://doi.org/10.1371/journal.pone.0123483. [Free online]
Note: This journalistic account of the research may also be useful.
  • Alperin, Juan Pablo, Erik Warren Hanson, Kenneth Shores, and Stefanie Haustein. 2017. “Twitter Bot Surveys: A Discrete Choice Experiment to Increase Response Rates.” In Proceedings of the 8th International Conference on Social Media & Society, 1–4. #SMSociety17. Toronto, ON, Canada: Association for Computing Machinery. https://doi.org/10.1145/3097286.3097313. [Available through UW libraries]

Optional Readings:

  • Van Selm, Martine, and Nicholas W. Jankowski. 2006. “Conducting Online Surveys.” Quality and Quantity 40 (3): 435–56. https://doi.org/10.1007/s11135-005-8081-8. [Available through UW Libraries]
  • Vehovar, Vasja, and Katja Lozar Manfreda. 2017. “Overview: Online Surveys.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 143–61. London, UK: SAGE. [Available in Canvas]
  • Kaczmirek, Lars. 2017. “Online Survey Software.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 203–19. London, UK: SAGE. [Available in Canvas]
  • Toepoel, Vera. 2017. “Online Survey Design.” In The SAGE Handbook of Online Research Methods, edited by Nigel G. Fielding, Raymond M. Lee, and Grant Blank, 2 edition, 184–202. London, UK: SAGE. [Available in Canvas]
  • Mavletova, Aigul, and Mick P. Couper. 2014. “Mobile Web Survey Design: Scrolling versus Paging, SMS versus E-Mail Invitations.” Journal of Survey Statistics and Methodology 2 (4): 498–518. https://doi.org/10.1093/jssam/smu015. [Available through UW libraries]'
  • Yun, Gi Woong, and Craig W. Trumbo. 2000. “Comparative Response to a Survey Executed by Post, e-Mail, & Web Form.” Journal of Computer-Mediated Communication 6 (1): 0–0. https://doi.org/10.1111/j.1083-6101.2000.tb00112.x. [Free online]
  • Hargittai, Eszter, and Chris Karr. 2009. “WAT R U DOIN? Studying the Thumb Generation Using Text Messaging.” In Research Confidential: Solutions to Problems Most Social Scientists Pretend They Never Have, edited by Eszter Hargittai, 192–216. Ann Arbor, MI: University of Michigan Press. [Available in Canvas]

If you don't have a background in survey design, these two have been recommended by our guest speaker as good basic things to read:

  • Krosnick, Jon A. 1999. “Maximizing Measurement Quality: Principles of Good Questionnaire Design.” In Measures of Political Attitudes, edited by John P. Robinson, Phillip R. Shaver, and Lawrence S. Wrightsman. New York: Academic Press.
  • Krosnick, Jon A. 1999. “Survey Research.” Annual Review of Psychology 50 (1): 537–67. https://doi.org/10.1146/annurev.psych.50.1.537. [Available through UW libraries]

Tools for doing mobile surveys:

Part II: Experiments[edit]

Required Readings:

Optional Readings:

This piece is set as the intersection of networks and experiments. It's very important but is probably too technical to assign for the whole c.ass
  • Kohavi, Ron, Alex Deng, Brian Frasca, Toby Walker, Ya Xu, and Nils Pohlmann. 2013. “Online Controlled Experiments at Large Scale.” In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1168–1176. KDD ’13. Chicago, Illinois, USA: Association for Computing Machinery. https://doi.org/10.1145/2487575.2488217. [Available through UW libraries]'
  • Reinecke, Katharina, and Krzysztof Z. Gajos. 2015. “LabintheWild: Conducting Large-Scale Online Experiments With Uncompensated Samples.” In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, 1364–1378. CSCW ’15. New York, NY, USA: ACM. https://doi.org/10.1145/2675133.2675246. [Available through UW libraries]'
  • Zhu, Haiyi, Amy Zhang, Jiping He, Robert E. Kraut, and Aniket Kittur. 2013. “Effects of Peer Feedback on Contribution: A Field Experiment in Wikipedia.” In , 2253. ACM Press. https://doi.org/10.1145/2470654.2481311. [Available through UW libraries]'
  • Zhang, Xiaoquan (Michael), and Feng Zhu. 2011. “Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia.” American Economic Review 101 (4): 1601–15. https://doi.org/10.1257/aer.101.4.1601. [Available through UW libraries]'
  • Weninger, Tim, Thomas James Johnston, and Maria Glenski. 2015. “Random Voting Effects in Social-Digital Spaces: A Case Study of Reddit Post Submissions.” Pp. 293–297 in Proceedings of the 26th ACM Conference on Hypertext & Social Media, HT ’15. Guzelyurt, Northern Cyprus: Association for Computing Machinery.

Week 6: Tuesday February 11: Crowdsourcing, Digital Labor Markets, and Human Computation[edit]

Note: I've marked things as [Required] below if they are required because I thought it made more sense to keep the topics groups of articles below intact.

MTurk documentation and guidelines:

Overviews of MTurk and issues of data quality:

Culture and work conditions for Turkers:

Systems to approve Turker experiences:

  • Salehi, Niloufar, Lilly C. Irani, Michael S. Bernstein, Ali Alkhatib, Eva Ogbe, Kristy Milland, and Clickhappier. 2015. “We Are Dynamo: Overcoming Stalling and Friction in Collective Action for Crowd Workers.” In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1621–1630. CHI ’15. Seoul, Republic of Korea: Association for Computing Machinery. https://doi.org/10.1145/2702123.2702508. [Available from UW libraries]
  • Irani, Lilly C., and M. Six Silberman. 2013. “Turkopticon: Interrupting Worker Invisibility in Amazon Mechanical Turk.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 611–620. CHI ’13. Paris, France: Association for Computing Machinery. https://doi.org/10.1145/2470654.2470742. [Available from UW libraries]

Assignments to complete before class:

The first task is to complete a task a crowd worker:

  • If you are a US citizen: Sign up as a worker on MTurk. Find and complete at least 5 "hits" as a worker on Amazon Mechanical Turk. Note that to do this you will need to create a worker account on Mturk.
  • If you are not a US citizen or if you cannot sign up on MTurk for some other reason: Complete at least 3-4 classification tasks in at least 2 different Zooniverse projects of your choice. Also, complete at least one "study" in Lab in the Wild
  • In either case: Record (write down) details and notes about your tasks: What did you do? Who was the requester? What could you was the purpose of the task (as best you could tell)? What was the experience like? What research applications can you (not) imagine for this kind of system?

The second task is to get ready to launch a task as a requestor. We will design and launch tasks in class but I want you to do the following ahead of time:

  • Create a "requester" account on Amazon Mechnical Turk. Doing so may require up top 48 hours to be approved so please do that immediately so you have it ready to go in class.
  • Put money onto your requestor account to pay workers. A $5 budget should be sufficient for our class. They should take any payment that Amazon does.
  • Think of at least one small classification or coding task (e.g., of Tweets, images, etc) and one human subjects data collection tasks like a survey, a survey experiment, etc, that you would like to run. You will have a budget of $5 to run the task!
  • If running this task will involve some data (e.g., a set of images or URLs, a set of Tweets, etc), collect that material in a spreadsheet before class. If it will involve a survey, create your survey in a Google Form and/or a Survey Monkey or Qualtrics survey before class.

Week 6: Saturday February 15: CDSW Session 3[edit]

As description in the section on technical skills above, I expect everybody who is not comfortable with at least basic programming and data collection to attend the Community Data Science Workshops (Winter 2020) which I am running concurrently with this class.

This session will run from 9am-3pm. Details on the CDSW Winter 2020 page.

Week 7: Tuesday February 18: Consulting Week (i.e., no group meeting)[edit]

During this week, we not meet together. Instead, I will schedule one-on-one in person meetings of an hour with each student individually to catch up with you about your project and to work directly with you to resolve any technical issues you have run into with data collection, etc.

Week 8: Tuesday February 25: (I) Discourse Analysis and (II) Visual Analysis[edit]

Part I: Discourse Analysis[edit]

Required Readings:

Optional Readings:

Part II: Visual Analysis[edit]

Required Readings:

Optional Readings:

Note: This is a two-part (each part is one hour) lecture and tutorial by an expert in computer vision. I strongly recommend watching Part I. I think this gives you a good sense of the nature of the kinds of challenges that were (and still are) facing the field of computer vision and anybody trying to have their computer look at images.

These five papers are all technical approaches to doing image classification using datasets from Internet-based datasets of images like Flickr, Google Image Search, Google Street View, or Instagram. Each of these describes interesting and challenges technical issues. If you're interested, it would be a great idea to read these to get a sense for the state of the art and what is and isn't possible:

Week 9: Tuesday March 3: Consulting Week[edit]

During this week, we will not meet together. Instead, I will schedule one-on-one in-person meetings of an hour with each student individually to catch up with you about your project and to work directly with you to resolve any technical issues you have run into with data collected.

Week 10: Tuesday March 10: Final Presentations[edit]

Administrative Notes[edit]

Your Presence in Class[edit]

As detailed in the section on participation and in my page on assessment, class participation is a critical way that I will assess learning in the class. Obviously, you must be in class in order to participate. If you need to miss class for any reason, please contact me ahead of time (email is best). In the event of an absence, you are responsible for obtaining class notes, handouts, assignments, etc.

Office Hours[edit]

I will hold office hours on Thursdays 1-2 pm in Communications (CMU) 333. In addition to my scheduled office hours, I am generally in my lab in CMU 306. Feel free to stop by at any time or to contact me to arrange a time to meet.

Religious Accommodations[edit]

Washington state law requires that UW develop a policy for the accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.

Student Conduct[edit]

The University of Washington Student Conduct Code (WAC 478-121) defines prohibited academic and behavioral conduct and describes how the University holds students accountable as they pursue their academic goals. Allegations of misconduct by students may be referred to the appropriate campus office for investigation and resolution. More information can be found online at https://www.washington.edu/studentconduct/ Safety

Call SafeCampus at 206-685-7233 anytime–no matter where you work or study–to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support while discussing short- and long-term solutions and connecting you with additional resources when requested.

Academic Dishonesty[edit]

This includes: cheating on assignments, plagiarizing (misrepresenting work by another author as your own, paraphrasing or quoting sources without acknowledging the original author, or using information from the internet without proper citation), and submitting the same or similar paper to meet the requirements of more than one course without instructor approval. Academic dishonesty in any part of this course is grounds for failure and further disciplinary action. The first incident of plagiarism will result in the student’s receiving a zero on the plagiarized assignment. The second incident of plagiarism will result in the student’s receiving a zero in the class.

Disability Resources[edit]

If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to UW at your earliest convenience so we can discuss your needs in this course.

If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or uwdrs@uw.edu or disability.uw.edu. DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.

Other Student Support[edit]

Any student who has difficulty affording groceries or accessing sufficient food to eat every day, or who lacks a safe and stable place to live, and believes this may affect their performance in the course, is urged to contact the graduate program advisor for support. Furthermore, please notify the professors if you are comfortable in doing so. This will enable us to provide any resources that we may possess (adapted from Sara Goldrick-Rab). Please also note the student food pantry, Any Hungry Husky at the ECC.

Credit and Notes[edit]

This will be the third time I have taught this course at UW in its current form. This syllabus draws heavily from previous versions. Syllabuses from earlier classes can be found online at:

This syllabus was inspired by and borrows with permission from, a syllabus from an earlier version of this class taught by Kirsten Foot. Professor Foot last taught the course in Spring 2014.