Designing Internet Research (Spring 2025)

From CommunityData
Many weeks on the #Schedule have more readings listed than I plan to assign, and many will be made "optional" as the schedule shapes up. I've erred on the side of including more reading options to convey a sense of the material I am choosing from. The expected reading load is detailed in the #Workload section of this page.
COM528: Designing Internet Research - Department of Communication, University of Washington
Instructor:
Course Meetings: 4:30–6:20p, Tuesdays & Thursdays, in CMU 322
Course Websites:
  • Canvas: for announcements and turning in assignments
  • A group chat system of "our" choice: Discord? Slack? Element/Matrix? We will discuss this in the first class.
  • Everything else will be linked on this page.
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

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 that might include: web archiving; textual analysis; ethnography; interviews; network analyses of social and hyperlink networks; analysis of digital trace data; textual analysis; 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.

Note About This Syllabus

You should expect this syllabus to be a dynamic document, not a contract. Although the core expectations for this class are fixed, the details of readings and assignments will shift based on how the class goes, any guest speakers I arrange, my 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. 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 I don't change something marked "[Tentative]" before the deadline, then it is assigned. This also means that if you plan to read more than six days ahead, contact me first.
  • Because this syllabus is a wiki, you can track every change by clicking the history button on this page when I make changes. I will summarize these changes in the weekly announcement on Canvas that will be emailed to everybody in the class. Closely monitor your email or the announcements section on the course website on Canvas to ensure you don't miss these announcements.
  • I will frequently ask the class for voluntary, anonymous feedback, 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 the courses that I teach while the quarter progressed based on this feedback.

Readings

Because I understand and remember the financial challenges of being a student, I've structured this course so there is no textbook for this class. There is nothing you will need to purchase. Everything we'll read in this class will either be freely available online, through UW libraries, or via Canvas.

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]

Access to Readings

Many readings are marked as "[Available through UW libraries]". Most of these will be accessible to anybody who connects from the UW network. This means that if you're on campus, it will likely work. Although you can go through the UW libraries website to get most of these, the easiest way is using the UW library proxy bookmarklet. This is a little button you can drag and drop onto the bookmarks toolbar on your browser. When you press the button, it will ask you to log in using your UW NetID and then will automatically send your traffic through UW libraries. You can also use the other tools on this UW libraries webpage.

Some Reflections on Technical Skills

This course 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 than more "hard" technical skills like programming, web scraping, and so on. But they are ultimately what will make a research project interesting, useful, or valid.

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.

Because students are going to come to the class with different technical skillsets, I will not be devoting time in this class to developing technical skills. That said, I strongly believe that a well rounded Internet researcher will have these skills as well. Although being successful in this class will not also require technical skills, being a successful Internet researcher will.

For example, I think most Internet researchers should have at least:

  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. However, if you happen to known a statistical programming language, learning a language like Python will be much easier!
  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, Dedoose, Taguette, or similar.

If you are already comfortable doing these things, great. If you are not, I'd love to work with you to help you make a plan for building these skills. To be clear: It's not part of the class and it's not part of how you will be evaluated. But it's something that I want to help you all to have.

Here are some options for building these technical skills:

  • I can help point you to find some online resources like MOOCs, online tutorials, and so on that are useful for building these skills. The details will probably vary based on what you know already.
  • I have plans to teach a class (likely in the Spring quarter of 2023) that will be a sort of companion class to this one and which will introduce Python and the skills above. I'd love to have any of you join me!
  • I also regularly have organized free workshops called the Community Data Science Workshops that teach exactly these skills. Although I've historically tried to time these workshops with this class, the ongoing pandemic has meant that it isn't in the cards this quarter. I do hope to teach them again at some point in the near future, though and happy to put you all on the announcement list.

Workload

This class is a 5 credit class. According to the UW policy, students should expect to devote about 3 hours per week per credit—on average across weeks and students. With this in mind, I plan to assign about a book worth of reading each week. Because we will spend 3-4 hours in class and an hour or two on assignments, on average, I expect everybody to read for about 8-10 hours each week (i.e., about one book's worth of reading time). For some people, reading a book's worth of articles will take longer. For many, it will take less.

I understand this class involves a lot of reading compared to some other courses, especially outside of the social sciences. Historically, students suggest my courses take more time than most classes at UW but less time per week (on average) than 3 hours per credit. Please let me know if you are spending more than 15 hours a week on the class.

Schedule

Tuesday April 1: Introduction

Optional Readings:

  • Agre, Phil. 2004. “Internet Research: For and Against.” In Internet Research Annual: Selected Papers from the Association of Internet Researchers Conferences 2000-2002, edited by Mia Consalvo, Nancy Baym, Jeremy Hunsinger, Klaus Bruhn Jensen, John Logie, Monica Muerero, and Leslie Regan Shade. Vol. 1. New York: Peter Lang. http://polaris.gseis.ucla.edu/pagre/research.html. [Available free online]
  • Lazer, David, Alex Pentland, Lada Adamic, Sinan Aral, Albert-Laszlo Barabasi, Devon Brewer, Nicholas Christakis, et al. 2009. “Computational Social Science.” Science 323 (5915): 721–23. https://doi.org/10.1126/science.1167742. [Available from UW libraries]
  • 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]
  • 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]

Thursday April 3: Ethics

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]

Tuesday April 8: Internet Data Collection

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 from 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 from 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 from UW libraries]
  • Shumate, Michelle, and Matthew S. Weber. 2015. “The Art of Web Crawling for Social Science Research.” In Digital Research Confidential: The Secrets of Studying Behavior Online, edited by Eszter Hargittai and Christian Sandvig, 234–59. Cambridge, MA: The MIT Press. [Available in Canvas]

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.

Thursday April 10: Content Analysis and Sentiment Analysis

Required Readings:

This is a short encyclopedia article that defines content analysis. If you are at all unfamiliar with content analysis, please read this first, up until the section "Content Analysis Applications to Political Communication:

Then proceed to read these pieces:

Optional Readings:

I'm assuming you have at least a rough familiarity with content analysis as a methodology. These help provide more of a background into content analysis in general:

  • Neuendorf, Kimberly A. 2017. The Content Analysis Guidebook. 2nd ed. Thousand Oaks, CA: SAGE. [Available from Instructor]
  • Krippendorff, Klaus. 2018. Content Analysis: An Introduction to Its Methodology. 4th ed. SAGE Publications. [Available from Instructor]

Tuesday April 15: Inductive Textual Analysis & Discourse Analysis

Required Readings
Optional Readings

Thursday April 17: Agent-Based Simulation (Traditional & Generative)

Required Readings
Optional Readings
  • Wilensky, Uri, and William Rand. 2015. An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, Massachusetts: The MIT Press. [Available from instructor]
  • Park, Joon Sung, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein. 2023. “Generative Agents: Interactive Simulacra of Human Behavior.” In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, 1–22. UIST ’23. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3586183.3606763. [Available free online]

Tuesday April 22: Visual Analysis

Details and readings are still tentative.

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:

Thursday April 24: Digital & Trace Ethnography

Details and readings are still tentative.

Required Readings:

More traditional ethnographic research in online settings:

  • Hine, 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 from 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 from UW libraries]

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

  • Geiger, R. Stuart, and David Ribes. 2010. “The Work of Sustaining Order in Wikipedia:The Banning of a Vandal.” In Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work, 117–126. CSCW ’10. New York, NY, USA: ACM. https://doi.org/10.1145/1718918.1718941. [Available from UW libraries] — A trace ethnography and sort of the companion paper/substantive paper for the methods piece included in the required readings above.
  • Brotsky, Sarah R., and David Giles. 2007. “Inside the ‘Pro-Ana’ Community: A Covert Online Participant Observation.” Eating Disorders 15 (2): 93–109. https://doi.org/10.1080/10640260701190600. [Available from UW libraries]
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. [Available free online]
  • 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]

Tuesday April 29: Web-scraping

Details and readings are still tentative.

Thursday May 1: Online Interviewing

Details and readings are still tentative.

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 in 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 from UW libraries]
  • 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 from 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 from UW libraries]
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 from UW libraries]
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:

Tuesday May 6: Design Research

Details and readings are still tentative.

Required Readings:

Optional Readings:

  • Olsen, Dan R., Jr. 2007. “Evaluating User Interface Systems Research.” In Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology, 251–58. UIST ’07. New York, NY, USA: ACM. https://doi.org/10.1145/1294211.1294256. [Available from UW libraries]
  • Grudin, Jonathan. 1988. “Why CSCW Applications Fail: Problems in the Design and Evaluation of Organizational Interfaces.” In Proceedings of the 1988 ACM Conference on Computer-Supported Cooperative Work, 85–93. CSCW ’88. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/62266.62273. [Available from UW libraries]
  • Zhang, Amy X., Grant Hugh, and Michael S. Bernstein. 2020. “PolicyKit: Building Governance in Online Communities.” In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology, 365–78. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3379337.3415858. [Available from UW libraries]

Thursday May 8: Consulting Day

We will not meet together as a group today. 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.

Tuesday May 13: Consulting Day

We will not meet together as a group today. 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.

Thursday May 15: Experiments

Details and readings are still tentative.

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 from 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 from 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 from 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 from 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.

Tuesday May 20: Surveys

Details and readings are still tentative.


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. [Available 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. [Available 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. [Available 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 from 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 from 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 from 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. [Available 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 from UW libraries]

Tools for doing mobile surveys:

Thursday May 22: Social network analysis

Details and readings are still tentative.

Required Readings:

Optional Readings:

Network datasets:

Tuesday May 27: Consulting Day

We will not meet together as a group today. 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.

Thursday May 29: Consulting Day

We will not meet together as a group today. 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.

Tuesday June 3: Final Presentations

Thursday June 5: Final Presentations

Additional Topics

I've prepared more topics that we could reasonably cover. Material from those potential topics are included on the /Additional topics subpage. Topics include discourse analysis, human computation (e.g., Mechanical Turk), sensor data, and hyperlink networks.

Assignments

Your assignments consist of two major projects: (1) weekly response papers and in-class discussion, and (2) a final research project. Your grade in the course will be assessed in the #Grading and Assessment section of this page.

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).

Reflections

Deliverables
(1) Post a new message in the appropriate the discussion board in Canvas; (2) Respond to at least one of your classmates before class.
Due Date
(1) the day of class before 6:30am (on any day with reading); (2) the day of class by 3pm (on a day with reading)
Maximum length
500 words

This quarter includes 13 class sessions with required readings. As a result, you must each write 13 response papers that address the readings for each day of class with required reading. Response papers should be no more than 500 words (about one single-spaced pages). Please respect this maximum to manage the workload for yourself and others. So everyone will have a chance to incorporate them into their readings, response papers should be posted to our course website the day before (i.e., before 6:30am on Tuesday and Thursday) so that everybody can read and construct their responses before class.

Regarding content, response papers allow you to engage the readings by identifying common or conflicting premises, thinking through potential implications, offering supporting or conflicting examples, posing well-supported objections, or outlining critical extensions. Providing a short quote or two that directly engages the texts is often helpful. Please also pose one or two open-ended questions that may serve as jumping-off points for our in-class conversation. A good response paper will include minimal summarizing, at most, and focus more on responding to ideas. Justify your reflections with evidence from the text and beyond; for example, don't just say what you wonder about or find interesting without explaining why you find it interesting.

After you post your reflection, please read all of your classmates’ responses before class and briefly respond to a minimum of two of your classmates’ posts before 3pm on the day of class and nominate at least a question or two for discussion.

Final Project

For the final project, I want you to take what you've learned in the class and apply it to an original research project. 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 several forms including:

  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. If none of these approaches work for you, I'm willing to discuss other possible deliverables.

I am open to having folks select a fourth path for their final projects. In any case, I will want a clear set of deliverables articulated in writing as part of the #Final Project Identification assignment.

Final Project Identification

Due Date
April 18 23:59 PM
Maximum paper length
800 words (~3 pages)
Deliverables
Turn 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 Paper

Paper Due Date
June 13
Maximum final paper length
8000 words (~27 double-spaced 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 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 these details, feel free to start with a brief summary of the purpose and importance of this research, and an introduction to your research questions or hypotheses. If you provide more detail, that's fine, but I won't give you detailed feedback on these parts.

Whatever you choose to turn in for your final project should include:

  • a statement of the purpose, central focus, relevance and significance of your project;
  • 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 if applicable

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 in your paper. If collecting data for a proposed project is impractical (e.g., because of IRB applications, funding, etc.), let's talk. I would love for you to engage in the collection of public datasets as part of a pilot or formative study. If this is not feasible or useful, we can discuss other options.

I prefer that you write this paper individually, but I'm open to the idea that you may want to work with others in the class.

Outline / Draft
Due Date
May 23
All Deliverables
Turn in in the appropriate Canvas dropbox

I want you all to turn it an outline or draft several weeks before the final project so that we can discuss this in our final set of one-on-one consulting meetings. Although the specific format will vary based on the nature of your project and your progress on it, it should demonstrate major progress on your final deliverables for the class and provide an answer—in outline form—to every applicable item on the list in the #Final Project section above.

I you're looking for an outline format that is useful for writing papers, I typically use what my groups calls Matsuzaki outlines (and which are described in details on our wiki). The Matsuzaki outline is particularly well suited to quantitative social scientific work, and probably less good for others. That said, folks have used it successfully for a range of projects.

If you're looking for information on how to organize a quantitative academic paper in the social sciences, check out my page on the structure of a quantitative empirical research paper.

Final Presentation
Presentation Dates
June 3 and 5

More details will be posted about the expectations and format for final presentations closer to the deadline.

Grading and Assessment

The writing rubric section of the detailed page on assessment gives the rubric I will use to evaluate both your #Weekly Response Papers and your #Final Projects.

Your participation in the course will be assessed using my detailed User:Benjamin Mako Hill/Assessment#Participation Rubric. Please also pay close attention to the section on maintaining participation balance.

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:

  • Weekly response papers: 30%
  • Participation in class discussion: 20%
  • Fina project identification: 5%
  • Final project outline: 5%
  • Final project presentation: 10%
  • Final project paper: 30%

Administrative Notes

Office Hours

Office hours will be appointment—I'm usually available via chat during "business hours." You can view out my calendar and/or put yourself on it. If you schedule a meeting, we'll meet in the Jitsi room (makooffice). You will get a link to the room through the scheduling, although you should be able to find it by navigating through https://meet.jit.si.


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 Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.

Student Conduct

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.

Use of AI Tools

Unless otherwise noted, work submitted for this course must be your own. Unless otherwise specified, using generative AI tools, such as ChatGPT, when working on assignments is forbidden. Using generative AI outside of specified tasks will be considered academic misconduct and subject to investigation.

The assignments in this class have been designed to challenge you to develop creativity, critical thinking, and problem-solving skills. Using AI technology will limit your capacity to develop these skills and meet the learning goals of this course.

If you have any questions about what constitutes academic integrity in this course or at the University of Washington, please contact me to discuss your concerns.

Please note that I do not consider grammar/spellchecking a prohibited use of AI.

Text adapted from: UW sample syllabus statements.

Academic Dishonesty

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

If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations through their processes 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.

Mental Health

Your mental health is important. If you are feeling distressed, anxious, depressed, or in any way struggling with your emotional and psychological wellness, please know that you are not alone. College can be a profoundly difficult time for many of us.

Resources are available for you:

Other Student Support

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

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.

Retrieved from "https://wiki.communitydata.science/index.php?title=Designing_Internet_Research_(Spring_2025)&oldid=273938"
Attribution-Share Alike 3.0 Unported
Powered by MediaWiki