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22:40, 20 September 2018: 205.175.107.103 (talk) triggered filter 0, performing the action "edit" on Human Centered Data Science (Fall 2018)/Schedule. Actions taken: Disallow; Filter description: (examine)

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* Aragon, C. et al. (2016). [https://cscw2016hcds.files.wordpress.com/2015/10/cscw_2016_human-centered-data-science_workshop.pdf ''Developing a Research Agenda for Human-Centered Data Science.''] Human Centered Data Science workshop, CSCW 2016.
* Aragon, C. et al. (2016). [https://cscw2016hcds.files.wordpress.com/2015/10/cscw_2016_human-centered-data-science_workshop.pdf ''Developing a Research Agenda for Human-Centered Data Science.''] Human Centered Data Science workshop, CSCW 2016.
* Kling, Rob and Star, Susan Leigh. [https://scholarworks.iu.edu/dspace/bitstream/handle/2022/1798/wp97-04B.html ''Human Centered Systems in the Perspective of Organizational and Social Informatics.''] 1997.
* Kling, Rob and Star, Susan Leigh. [https://scholarworks.iu.edu/dspace/bitstream/handle/2022/1798/wp97-04B.html ''Human Centered Systems in the Perspective of Organizational and Social Informatics.''] 1997.
* Ideo.org [http://www.designkit.org/ ''The Field Guide to Human-Centered Design.''] 2015.


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'<noinclude> <div style="font-family:Rockwell,'Courier Bold',Courier,Georgia,'Times New Roman',Times,serif; min-width:10em;"> <div style="float:left; width:100%; margin-right:2%;"> {{Link/Graphic/Main/2 |highlight color= 27666b |color=460c40 |link= |image= |text-align=left |top font-size= 1.1em |top color=FFF |line color=FFF |top text=This page is a work in progress. |bottom font-size= 1em |bottom color= FFF |bottom text= |line= none }}</div></div> </noinclude> === Week 1: September 27 === [[HCDS_(Fall_2018)/Day_1_plan|Day 1 plan]] <!--[[:File:HCDS Week 1 slides.pdf|Day 1 slides]]--> ;Introduction to Human Centered Data Science: ''What is data science? What is human centered? What is human centered data science?'' ;Assignments due * fill out the pre-course survey * Read: Provost, Foster, and Tom Fawcett. [http://online.liebertpub.com/doi/pdf/10.1089/big.2013.1508 ''Data science and its relationship to big data and data-driven decision making.''] Big Data 1.1 (2013): 51-59. ('''no reading reflection required''') ;Agenda {{:HCDS (Fall 2018)/Day 1 plan}} ;Readings assigned * Read: Barocas, Solan and Nissenbaum, Helen. ''Big Data's End Run around Anonymity and Consent.'' In ''Privacy, Big Data, and the Public Good''. 2014. (PDF on Canvas) ;Homework assigned * Reading reflection ;Resources * Aragon, C. et al. (2016). [https://cscw2016hcds.files.wordpress.com/2015/10/cscw_2016_human-centered-data-science_workshop.pdf ''Developing a Research Agenda for Human-Centered Data Science.''] Human Centered Data Science workshop, CSCW 2016. * Kling, Rob and Star, Susan Leigh. [https://scholarworks.iu.edu/dspace/bitstream/handle/2022/1798/wp97-04B.html ''Human Centered Systems in the Perspective of Organizational and Social Informatics.''] 1997. * Ideo.org [http://www.designkit.org/ ''The Field Guide to Human-Centered Design.''] 2015. <br/> <hr/> <br/> === Week 2: October 4 === [[HCDS_(Fall_2018)/Day_2_plan|Day 2 plan]] <!-- [[:File:HCDS Week 2 slides.pdf|Day 2 slides]] --> ;Ethical considerations: ''privacy, informed consent and user treatment'' ;Assignments due *Week 1 reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 2 plan}} ;Readings assigned * Read: boyd, danah and Crawford, Kate, Six Provocations for Big Data (September 21, 2011). A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, September 2011. Available at SSRN: https://ssrn.com/abstract=1926431 or http://dx.doi.org/10.2139/ssrn.1926431 ;Homework assigned * Reading reflection * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|A1: Data curation]] ;Resources * National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. [https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html ''The Belmont Report.''] U.S. Department of Health and Human Services, 1979. * Markham, Annette and Buchanan, Elizabeth. [https://aoir.org/reports/ethics2.pdf ''Ethical Decision-Making and Internet Researchers.''] Association for Internet Research, 2012. * Hill, Kashmir. [https://www.forbes.com/sites/kashmirhill/2014/06/28/facebook-manipulated-689003-users-emotions-for-science/#6a01653e197c ''Facebook Manipulated 689,003 Users' Emotions For Science.''] Forbes, 2014. * Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. [http://www.pnas.org/content/111/24/8788.full ''Experimental evidence of massive-scale emotional contagion through social networks.''] PNAS 2014 111 (24) 8788-8790; published ahead of print June 2, 2014. * Barbaro, Michael and Zeller, Tom. [http://query.nytimes.com/gst/abstract.html?res=9E0CE3DD1F3FF93AA3575BC0A9609C8B63&legacy=true ''A Face Is Exposed for AOL Searcher No. 4417749.''] New York Times, 2008. * Zetter, Kim. [https://www.wired.com/2012/06/wmw-arvind-narayanan/ ''Arvind Narayanan Isn’t Anonymous, and Neither Are You.''] WIRED, 2012. * Gray, Mary. [http://culturedigitally.org/2014/07/when-science-customer-service-and-human-subjects-research-collide-now-what/ ''When Science, Customer Service, and Human Subjects Research Collide. Now What?''] Culture Digitally, 2014. * Tene, Omer and Polonetsky, Jules. [https://www.stanfordlawreview.org/online/privacy-paradox-privacy-and-big-data/ ''Privacy in the Age of Big Data.''] Stanford Law Review, 2012. * Dwork, Cynthia. [https://www.microsoft.com/en-us/research/wp-content/uploads/2008/04/dwork_tamc.pdf ''Differential Privacy: A survey of results'']. Theory and Applications of Models of Computation , 2008. * Hsu, Danny. [http://blog.datasift.com/2015/04/09/techniques-to-anonymize-human-data/ ''Techniques to Anonymize Human Data.''] Data Sift, 2015. * Metcalf, Jacob. [http://ethicalresolve.com/twelve-principles-of-data-ethics/ ''Twelve principles of data ethics'']. Ethical Resolve, 2016. <br/> <hr/> <br/> === Week 3: October 11 === [[HCDS_(Fall_2018)/Day_3_plan|Day 3 plan]] <!-- [[:File:HCDS Week 3 slides.pdf|Day 3 slides]] --> ;Reproducibility and Accountability: ''data curation, preservation, documentation, and archiving; best practices for open scientific research'' ;Assignments due * Week 2 reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 3 plan}} ;Readings assigned *Read: Chapter 2 [https://www.practicereproducibleresearch.org/core-chapters/2-assessment.html "Assessing Reproducibility"] and Chapter 3 [https://www.practicereproducibleresearch.org/core-chapters/3-basic.html "The Basic Reproducible Workflow Template"] from ''The Practice of Reproducible Research'' University of California Press, 2018. * Read: Hickey, Walt. [https://fivethirtyeight.com/features/the-dollar-and-cents-case-against-hollywoods-exclusion-of-women/ ''The Dollars and Cents Case Against Hollywood's Exclusion of Women.''] FiveThirtyEight, 2014. '''AND''' Keegan, Brian. [https://github.com/brianckeegan/Bechdel/blob/master/Bechdel_test.ipynb ''The Need for Openness in Data Journalism.''] 2014. ;Homework assigned * Reading reflection ;Examples of well-documented open research projects * Keegan, Brian. [https://github.com/brianckeegan/WeatherCrime ''WeatherCrime'']. GitHub, 2014. * Geiger, Stuart R. and Halfaker, Aaron. [https://github.com/halfak/are-the-bots-really-fighting ''Operationalizing conflict and cooperation between automated software agents in Wikipedia: A replication and expansion of "Even Good Bots Fight"'']. GitHub, 2017. * Narayan, Sneha et al. [https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6HPRIG ''Replication Data for: The Wikipedia Adventure: Field Evaluation of an Interactive Tutorial for New Users'']. Harvard Dataverse, 2017. * * Warnke-Wang, Morten. ''[https://meta.wikimedia.org/wiki/Research:Autoconfirmed_article_creation_trial Autoconfirmed article creation trial].'' Wikimedia, 2017. ;Examples of not-so-well documented open research projects * Eclarke. [https://github.com/eclarke/swga_paper SWGA paper]. GitHub, 2016. * David Lefevre. [https://figshare.com/articles/Lefevre_and_Cox_Delayed_instructional_feedback_may_be_more_effective_but_is_this_contrary_to_learners_preferences_/2061303 ''Lefevre and Cox: Delayed instructional feedback may be more effective, but is this contrary to learners’ preferences?''] Figshare, 2016. * Alneberg. [https://github.com/BinPro/paper-data ''CONCOCT Paper Data'']. GitHub, 2014. ;Other resources * Press, Gil. [https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#2608257f6f63 ''Cleaning Big Data: Most Time-Consuming, Least Enjoyable Data Science Task, Survey Says.''] Forbes, 2016. * Christensen, Garret. [https://github.com/garretchristensen/BestPracticesManual/blob/master/Manual.pdf ''Manual of Best Practices in Transparent Social Science Research.''] 2016. * Hickey, Walt. [https://fivethirtyeight.com/features/the-bechdel-test-checking-our-work/ ''The Bechdel Test: Checking Our Work'']. FiveThirtyEight, 2014. * Chapman et al. [ftp://ftp.software.ibm.com/software/analytics/spss/support/Modeler/Documentation/14/UserManual/CRISP-DM.pdf ''Cross Industry Standard Process for Data Mining'']. IBM, 2000. <br/> <hr/> <br/> === Week 4: October 18 === [[HCDS_(Fall_2018)/Day_4_plan|Day 4 plan]] <!-- [[:File:HCDS Week 4 slides.pdf|Day 4 slides]] --> ;Interrogating datasets: ''bias in data; best practices for selecting, describing, and implementing training data'' ;Assignments due * Reading reflection * A1: Data curation ;Agenda {{:HCDS (Fall 2018)/Day 4 plan}} ;Readings assigned * Read: Duarte, N., Llanso, E., & Loup, A. (2018). Mixed Messages? The Limits of Automated Social Media Content Analysis. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 81, 106. PDF: http://proceedings.mlr.press/v81/duarte18a.html * Read: Bender, E. M., & Friedman, B. (2018). Data Statements for NLP: Toward Mitigating System Bias and Enabling Better Science. T0 appear in Transactions of the ACL. PDF: https://openreview.net/forum?id=By4oPeX9f ;Homework assigned * Reading reflection * A2: Bias in data ;Resources * Aschwanden, Christie. [https://fivethirtyeight.com/features/science-isnt-broken/ ''Science Isn't Broken''] FiveThirtyEight, 2015. * Shyong (Tony) K. Lam, Anuradha Uduwage, Zhenhua Dong, Shilad Sen, David R. Musicant, Loren Terveen, and John Riedl. 2011. ''[http://files.grouplens.org/papers/wp-gender-wikisym2011.pdf WP:clubhouse?: an exploration of Wikipedia's gender imbalance.]'' In Proceedings of the 7th International Symposium on Wikis and Open Collaboration (WikiSym '11). ACM, New York, NY, USA, 1-10. DOI=http://dx.doi.org/10.1145/2038558.2038560 * Shilad Sen, Margaret E. Giesel, Rebecca Gold, Benjamin Hillmann, Matt Lesicko, Samuel Naden, Jesse Russell, Zixiao (Ken) Wang, and Brent Hecht. 2015. ''[http://www-users.cs.umn.edu/~bhecht/publications/goldstandards_CSCW2015.pdf Turkers, Scholars, "Arafat" and "Peace": Cultural Communities and Algorithmic Gold Standards]''. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '15). DOI: http://dx.doi.org/10.1145/2675133.2675285 <br/> <hr/> <br/> === Week 5: October 25 === [[HCDS_(Fall_2018)/Day_5_plan|Day 5 plan]] <!-- [[:File:HCDS Week 5 slides.pdf|Day 5 slides]] --> ;Introduction to mixed-methods research: ''Big data vs thick data; integrating qualitative research methods into data science practice'' ;Assignments due * Reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 5 plan}} ;Readings assigned * R. Stuart Geiger and Aaron Halfaker. 2017. ''[https://commons.wikimedia.org/wiki/File:conflict-bots-wp-cscw.pdf Operationalizing conflict and cooperation between automated software agents in Wikipedia: A replication and expansion of Even Good Bots Fight]''. Proceedings of the ACM on Human-Computer Interaction (Nov 2017 issue, CSCW 2018 Online First) 1, 2, Article 49. DOI: https://doi.org/10.1145/3134684 ;Homework assigned * Reading reflection * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A3:_Crowdwork_ethnography|A3: Crowdwork ethnography]] ;Resources * WeArDynamo contributors. ''[http://wiki.wearedynamo.org/index.php?title=Basics_of_how_to_be_a_good_requester How to be a good requester]'' and ''[http://wiki.wearedynamo.org/index.php?title=Guidelines_for_Academic_Requesters Guidelines for Academic Requesters]''. Wearedynamo.org * Wang, Tricia. ''[https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7 Why Big Data Needs Thick Data]''. Ethnography Matters, 2016. * Maximillian Klein. ''[http://whgi.wmflabs.org/gender-by-language.html Gender by Wikipedia Language]''. Wikidata Human Gender Indicators (WHGI), 2017. * Benjamin Collier and Julia Bear. ''[https://static1.squarespace.com/static/521c8817e4b0dca2590b4591/t/523745abe4b05150ff027a6e/1379354027662/2012+-+Collier%2C+Bear+-+Conflict%2C+confidence%2C+or+criticism+an+empirical+examination+of+the+gender+gap+in+Wikipedia.pdf Conflict, criticism, or confidence: an empirical examination of the gender gap in wikipedia contributions]''. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work (CSCW '12). DOI: https://doi.org/10.1145/2145204.2145265 * Christina Shane-Simpson, Kristen Gillespie-Lynch, Examining potential mechanisms underlying the Wikipedia gender gap through a collaborative editing task, In Computers in Human Behavior, Volume 66, 2017, https://doi.org/10.1016/j.chb.2016.09.043. (PDF on Canvas) * Amanda Menking and Ingrid Erickson. 2015. ''[https://upload.wikimedia.org/wikipedia/commons/7/77/The_Heart_Work_of_Wikipedia_Gendered,_Emotional_Labor_in_the_World%27s_Largest_Online_Encyclopedia.pdf The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia]''. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). https://doi.org/10.1145/2702123.2702514 * Kevin Crowston and the Gravity Spy Team. 2017. ''[https://crowston.syr.edu/sites/crowston.syr.edu/files/cpa137-crowstonA.pdf Gravity Spy: Humans, Machines and The Future of Citizen Science].'' In Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17 Companion). ACM, New York, NY, USA, 163-166. DOI: https://doi.org/10.1145/3022198.3026329 <br/> <hr/> <br/> === Week 6: November 1 === [[HCDS_(Fall_2018)/Day_6_plan|Day 6 plan]] <!-- [[:File:HCDS Week 6 slides.pdf|Day 6 slides]] --> ;Interrogating algorithms: ''algorithmic fairness, transparency, and accountability; methods and contexts for algorithmic audits'' ;Assignments due * Reading reflection * A2: Bias in data ;Agenda {{:HCDS (Fall 2018)/Day 6 plan}} ;Readings assigned * Read: Christian Sandvig, Kevin Hamilton, Karrie Karahalios, Cedric Langbort (2014/05/22) ''[http://www-personal.umich.edu/~csandvig/research/Auditing%20Algorithms%20--%20Sandvig%20--%20ICA%202014%20Data%20and%20Discrimination%20Preconference.pdf Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms].'' Paper presented to "Data and Discrimination: Converting Critical Concerns into Productive Inquiry," a preconference at the 64th Annual Meeting of the International Communication Association. May 22, 2014; Seattle, WA, USA. * Read: Diakopoulos, N. (2014). Algorithmic accountability reporting: On the investigation of black boxes. Tow Center for Digital Journalism, 1–33. https://doi.org/10.1002/ejoc.201200111 ;Homework assigned * Reading reflection ;Resources * Hill, Kashmir. ''[https://gizmodo.com/facebook-figured-out-my-family-secrets-and-it-wont-tel-1797696163 Facebook figured out my family secrets, and it won't tell me how].'' Engadget, 2017. * Blue, Violet. ''[https://www.engadget.com/2017/09/01/google-perspective-comment-ranking-system/ Google’s comment-ranking system will be a hit with the alt-right].'' Engadget, 2017. * Ingold, David and Soper, Spencer. ''[https://www.bloomberg.com/graphics/2016-amazon-same-day/ Amazon Doesn’t Consider the Race of Its Customers. Should It?].'' Bloomberg, 2016. * Paul Lamere. ''[https://musicmachinery.com/2011/05/14/how-good-is-googles-instant-mix/ How good is Google's Instant Mix?].'' Music Machinery, 2011. * Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner. ''[https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias: Risk Assessment in Criminal Sentencing]. Propublica, May 2018. <!-- * Mars, Roman. ''[https://99percentinvisible.org/episode/the-age-of-the-algorithm/ The Age of the Algorithm].'' 99% Invisible Podcast, 2017. * [https://www.perspectiveapi.com/#/ Google's Perspective API] --> <br/> <hr/> <br/> === Week 7: November 8 === [[HCDS_(Fall_2018)/Day_7_plan|Day 7 plan]] ;Critical approaches to data science: ''power, data, and society; ethics of crowdwork'' ;Assignments due * Reading reflection * A3: Crowdwork ethnography ;Agenda {{:HCDS (Fall 2018)/Day 7 plan}} ;Readings assigned (read both, reflect on one) * TBD ;Homework assigned * Reading reflection * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A4:_Final_project_plan|A4: Final project plan]] ;Resources * Neff, G., Tanweer, A., Fiore-Gartland, B., & Osburn, L. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science. Big Data, 5(2), 85–97. https://doi.org/10.1089/big.2016.0050 * Lilly C. Irani and M. Six Silberman. 2013. ''[https://escholarship.org/content/qt10c125z3/qt10c125z3.pdf Turkopticon: interrupting worker invisibility in amazon mechanical turk]''. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). DOI: https://doi.org/10.1145/2470654.2470742 * Bivens, R. and Haimson, O.L. 2016. ''[http://journals.sagepub.com/doi/pdf/10.1177/2056305116672486 Baking Gender Into Social Media Design: How Platforms Shape Categories for Users and Advertisers]''. Social Media + Society. 2, 4 (2016), 205630511667248. DOI:https://doi.org/10.1177/2056305116672486. * Schlesinger, A. et al. 2017. ''[http://arischlesinger.com/wp-content/uploads/2017/03/chi2017-schlesinger-intersectionality.pdf Intersectional HCI: Engaging Identity through Gender, Race, and Class].'' Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17. (2017), 5412–5427. DOI:https://doi.org/10.1145/3025453.3025766. <br/> <hr/> <br/> === Week 8: November 15 === [[HCDS_(Fall_2018)/Day_8_plan|Day 8 plan]] <!-- [[:File:HCDS Week 8 slides.pdf|Day 8 slides]] --> ;Human-centered algorithm design: ''algorithmic interpretibility; human-centered methods for designing and evaluating algorithmic systems'' ;Assignments due * Reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 8 plan}} ;Readings assigned * Read: Baumer, E. P. S. (2017). Toward human-centered algorithm design. Big Data & Society, 4(2), 2053951717718854. https://doi.org/10.1177/2053951717718854 * Read: Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014). Power to the People: The Role of Humans in Interactive Machine Learning. AI Magazine, 35(4), 105. https://doi.org/10.1609/aimag.v35i4.2513 ;Homework assigned * Reading reflection ;Resources *Michael D. Ekstrand, F. Maxwell Harper, Martijn C. Willemsen, and Joseph A. Konstan. 2014. ''[https://md.ekstrandom.net/research/pubs/listcmp/listcmp.pdf User perception of differences in recommender algorithms].'' In Proceedings of the 8th ACM Conference on Recommender systems (RecSys '14). ACM, New York, NY, USA, 161-168. DOI: https://doi.org/10.1145/2645710.2645737 * Sean M. McNee, John Riedl, and Joseph A. Konstan. 2006. ''[http://files.grouplens.org/papers/mcnee-chi06-hri.pdf Making recommendations better: an analytic model for human-recommender interaction].'' In CHI '06 Extended Abstracts on Human Factors in Computing Systems (CHI EA '06). ACM, New York, NY, USA, 1103-1108. DOI=http://dx.doi.org/10.1145/1125451.1125660 * Sean M. McNee, Nishikant Kapoor, and Joseph A. Konstan. 2006. ''[http://files.grouplens.org/papers/p171-mcnee.pdf Don't look stupid: avoiding pitfalls when recommending research papers].'' In Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work (CSCW '06). ACM, New York, NY, USA, 171-180. DOI=http://dx.doi.org/10.1145/1180875.1180903 * Michael D. Ekstrand and Martijn C. Willemsen. 2016. ''[https://md.ekstrandom.net/research/pubs/behaviorism/BehaviorismIsNotEnough.pdf Behaviorism is Not Enough: Better Recommendations through Listening to Users].'' In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys '16). ACM, New York, NY, USA, 221-224. DOI: https://doi.org/10.1145/2959100.2959179 * Jess Holbrook. ''[https://medium.com/google-design/human-centered-machine-learning-a770d10562cd Human Centered Machine Learning].'' Google Design Blog. 2017. * Anderson, Carl. ''[https://medium.com/@leapingllamas/the-role-of-model-interpretability-in-data-science-703918f64330 The role of model interpretability in data science].'' Medium, 2016. <br/> <hr/> <br/> === Week 9: November 22 (No Class Session)=== [[HCDS_(Fall_2018)/Day_8_plan|Day 9 plan]] ;Data science for social good: ''Community-based and participatory approaches to data science; Using data science for society's benefit'' ;Assignments due * Reading reflection * A4: Final project plan ;Agenda {{:HCDS (Fall 2018)/Day 9 plan}} ;Readings assigned (Read and reflect on '''''one only''''') * Hill, B. M., Dailey, D., Guy, R. T., Lewis, B., Matsuzaki, M., & Morgan, J. T. (2017). Democratizing Data Science: The Community Data Science Workshops and Classes. In N. Jullien, S. A. Matei, & S. P. Goggins (Eds.), ''Big Data Factories: Scientific Collaborative approaches for virtual community data collection, repurposing, recombining, and dissemination''. New York, New York: Springer Nature. [[https://mako.cc/academic/hill_etal-cdsw_chapter-DRAFT.pdf Preprint/Draft PDF]] * Berney, Rachel, Bernease Herman, Gundula Proksch, Hillary Dawkins, Jacob Kovacs, Yahui Ma, Jacob Rich, and Amanda Tan. ''[https://dssg.uchicago.edu/wp-content/uploads/2017/09/berney.pdf Visualizing Equity: A Data Science for Social Good Tool and Model for Seattle].'' Data Science for Social Good Conference, September 2017, Chicago, Illinois USA (2017). ;Homework assigned * Reading reflection ;Resources * Daniela Aiello, Lisa Bates, et al. [https://shelterforce.org/2018/08/22/eviction-lab-misses-the-mark/ Eviction Lab Misses the Mark], ShelterForce, August 2018. <br/> <hr/> <br/> === Week 10: November 29 === [[HCDS_(Fall_2018)/Day_10_plan|Day 10 plan]] <!-- [[:File:HCDS Week 10 slides.pdf|Day 10 slides]] --> ;User experience and big data: ''Design considerations for machine learning applications; human centered data visualization; data storytelling'' ;Assignments due * Reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 10 plan}} ;Readings assigned * Megan Risdal, ''[http://blog.kaggle.com/2016/06/29/communicating-data-science-a-guide-to-presenting-your-work/ Communicating data science: a guide to presenting your work].'' Kaggle blog, 2016. * Marilynn Larkin, ''[https://www.elsevier.com/connect/how-to-give-a-dynamic-scientific-presentation How to give a dynamic scientific presentation].'' Elsevier Connect, 2015. ;Homework assigned * Reading reflection * A5: Final presentation ;Resources * Bart P. Knijnenburg, Martijn C. Willemsen, Zeno Gantner, Hakan Soncu, and Chris Newell. 2012. ''[https://pure.tue.nl/ws/files/3484177/724656348730405.pdf Explaining the user experience of recommender systems].'' User Modeling and User-Adapted Interaction 22, 4-5 (October 2012), 441-504. DOI=http://dx.doi.org/10.1007/s11257-011-9118-4 * Megan Risdal, ''[http://blog.kaggle.com/2016/08/10/communicating-data-science-why-and-some-of-the-how-to-visualize-information/ Communicating data science: Why and how to visualize information].'' Kaggle blog, 2016. * Megan Risdal, ''[http://blog.kaggle.com/2016/06/13/communicating-data-science-an-interview-with-a-storytelling-expert-tyler-byers/ Communicating data science: an interview with a storytelling expert].'' Kaggle blog, 2016. * Richard Garber, ''[https://joyfulpublicspeaking.blogspot.com/2010/08/power-of-brief-speeches-world-war-i-and.html Power of brief speeches: World War I and the Four Minute Men].'' Joyful Public Speaking, 2010. * Brent Dykes, ''[https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ Data Storytelling: The Essential Data Science Skill Everyone Needs].'' Forbes, 2016. * Xavier Amatriain and Justin Basilico. ''[https://medium.com/netflix-techblog/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429 Netflix Recommendations: Beyond the 5 stars].'' Netflix Tech Blog, 2012. *Fabien Girardin. ''[https://medium.com/@girardin/experience-design-in-the-machine-learning-era-e16c87f4f2e2 Experience design in the machine learning era].'' Medium, 2016. * Chen, N., Brooks, M., Kocielnik, R., Hong, R., Smith, J., Lin, S., Qu, Z., Aragon, C. ''[https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1254&context=hicss-50 Lariat: A visual analytics tool for social media researchers to explore Twitter datasets].'' Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS), Data Analytics and Data Mining for Social Media Minitrack (2017) <br/> <hr/> <br/> === Week 11: December 6 === [[HCDS_(Fall_2018)/Day_11_plan|Day 11 plan]] ;Final presentations: course wrap up, presentation of student projects'' ;Assignments due * Reading reflection * A5: Final presentation ;Agenda {{:HCDS (Fall 2018)/Day 11 plan}} ;Readings assigned * none! ;Homework assigned * none! ;Resources * ''one'' <br/> <hr/> <br/> === Week 12: Finals Week (No Class Session) === * NO CLASS * A6: FINAL PROJECT REPORT DUE BY 11:59PM on Sunday, December 9 * LATE PROJECT SUBMISSIONS NOT ACCEPTED. [[Category:HCDS (Fall 2018)]]'
New page wikitext, after the edit (new_wikitext)
'<noinclude> <div style="font-family:Rockwell,'Courier Bold',Courier,Georgia,'Times New Roman',Times,serif; min-width:10em;"> <div style="float:left; width:100%; margin-right:2%;"> {{Link/Graphic/Main/2 |highlight color= 27666b |color=460c40 |link= |image= |text-align=left |top font-size= 1.1em |top color=FFF |line color=FFF |top text=This page is a work in progress. |bottom font-size= 1em |bottom color= FFF |bottom text= |line= none }}</div></div> </noinclude> === Week 1: September 27 === [[HCDS_(Fall_2018)/Day_1_plan|Day 1 plan]] <!--[[:File:HCDS Week 1 slides.pdf|Day 1 slides]]--> ;Introduction to Human Centered Data Science: ''What is data science? What is human centered? What is human centered data science?'' ;Assignments due * fill out the pre-course survey * Read: Provost, Foster, and Tom Fawcett. [http://online.liebertpub.com/doi/pdf/10.1089/big.2013.1508 ''Data science and its relationship to big data and data-driven decision making.''] Big Data 1.1 (2013): 51-59. ('''no reading reflection required''') ;Agenda {{:HCDS (Fall 2018)/Day 1 plan}} ;Readings assigned * Read: Barocas, Solan and Nissenbaum, Helen. ''Big Data's End Run around Anonymity and Consent.'' In ''Privacy, Big Data, and the Public Good''. 2014. (PDF on Canvas) ;Homework assigned * Reading reflection ;Resources * Aragon, C. et al. (2016). [https://cscw2016hcds.files.wordpress.com/2015/10/cscw_2016_human-centered-data-science_workshop.pdf ''Developing a Research Agenda for Human-Centered Data Science.''] Human Centered Data Science workshop, CSCW 2016. * Kling, Rob and Star, Susan Leigh. [https://scholarworks.iu.edu/dspace/bitstream/handle/2022/1798/wp97-04B.html ''Human Centered Systems in the Perspective of Organizational and Social Informatics.''] 1997. <br/> <hr/> <br/> === Week 2: October 4 === [[HCDS_(Fall_2018)/Day_2_plan|Day 2 plan]] <!-- [[:File:HCDS Week 2 slides.pdf|Day 2 slides]] --> ;Ethical considerations: ''privacy, informed consent and user treatment'' ;Assignments due *Week 1 reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 2 plan}} ;Readings assigned * Read: boyd, danah and Crawford, Kate, Six Provocations for Big Data (September 21, 2011). A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, September 2011. Available at SSRN: https://ssrn.com/abstract=1926431 or http://dx.doi.org/10.2139/ssrn.1926431 ;Homework assigned * Reading reflection * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|A1: Data curation]] ;Resources * National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. [https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html ''The Belmont Report.''] U.S. Department of Health and Human Services, 1979. * Markham, Annette and Buchanan, Elizabeth. [https://aoir.org/reports/ethics2.pdf ''Ethical Decision-Making and Internet Researchers.''] Association for Internet Research, 2012. * Hill, Kashmir. [https://www.forbes.com/sites/kashmirhill/2014/06/28/facebook-manipulated-689003-users-emotions-for-science/#6a01653e197c ''Facebook Manipulated 689,003 Users' Emotions For Science.''] Forbes, 2014. * Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. [http://www.pnas.org/content/111/24/8788.full ''Experimental evidence of massive-scale emotional contagion through social networks.''] PNAS 2014 111 (24) 8788-8790; published ahead of print June 2, 2014. * Barbaro, Michael and Zeller, Tom. [http://query.nytimes.com/gst/abstract.html?res=9E0CE3DD1F3FF93AA3575BC0A9609C8B63&legacy=true ''A Face Is Exposed for AOL Searcher No. 4417749.''] New York Times, 2008. * Zetter, Kim. [https://www.wired.com/2012/06/wmw-arvind-narayanan/ ''Arvind Narayanan Isn’t Anonymous, and Neither Are You.''] WIRED, 2012. * Gray, Mary. [http://culturedigitally.org/2014/07/when-science-customer-service-and-human-subjects-research-collide-now-what/ ''When Science, Customer Service, and Human Subjects Research Collide. Now What?''] Culture Digitally, 2014. * Tene, Omer and Polonetsky, Jules. [https://www.stanfordlawreview.org/online/privacy-paradox-privacy-and-big-data/ ''Privacy in the Age of Big Data.''] Stanford Law Review, 2012. * Dwork, Cynthia. [https://www.microsoft.com/en-us/research/wp-content/uploads/2008/04/dwork_tamc.pdf ''Differential Privacy: A survey of results'']. Theory and Applications of Models of Computation , 2008. * Hsu, Danny. [http://blog.datasift.com/2015/04/09/techniques-to-anonymize-human-data/ ''Techniques to Anonymize Human Data.''] Data Sift, 2015. * Metcalf, Jacob. [http://ethicalresolve.com/twelve-principles-of-data-ethics/ ''Twelve principles of data ethics'']. Ethical Resolve, 2016. <br/> <hr/> <br/> === Week 3: October 11 === [[HCDS_(Fall_2018)/Day_3_plan|Day 3 plan]] <!-- [[:File:HCDS Week 3 slides.pdf|Day 3 slides]] --> ;Reproducibility and Accountability: ''data curation, preservation, documentation, and archiving; best practices for open scientific research'' ;Assignments due * Week 2 reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 3 plan}} ;Readings assigned *Read: Chapter 2 [https://www.practicereproducibleresearch.org/core-chapters/2-assessment.html "Assessing Reproducibility"] and Chapter 3 [https://www.practicereproducibleresearch.org/core-chapters/3-basic.html "The Basic Reproducible Workflow Template"] from ''The Practice of Reproducible Research'' University of California Press, 2018. * Read: Hickey, Walt. [https://fivethirtyeight.com/features/the-dollar-and-cents-case-against-hollywoods-exclusion-of-women/ ''The Dollars and Cents Case Against Hollywood's Exclusion of Women.''] FiveThirtyEight, 2014. '''AND''' Keegan, Brian. [https://github.com/brianckeegan/Bechdel/blob/master/Bechdel_test.ipynb ''The Need for Openness in Data Journalism.''] 2014. ;Homework assigned * Reading reflection ;Examples of well-documented open research projects * Keegan, Brian. [https://github.com/brianckeegan/WeatherCrime ''WeatherCrime'']. GitHub, 2014. * Geiger, Stuart R. and Halfaker, Aaron. [https://github.com/halfak/are-the-bots-really-fighting ''Operationalizing conflict and cooperation between automated software agents in Wikipedia: A replication and expansion of "Even Good Bots Fight"'']. GitHub, 2017. * Narayan, Sneha et al. [https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6HPRIG ''Replication Data for: The Wikipedia Adventure: Field Evaluation of an Interactive Tutorial for New Users'']. Harvard Dataverse, 2017. * * Warnke-Wang, Morten. ''[https://meta.wikimedia.org/wiki/Research:Autoconfirmed_article_creation_trial Autoconfirmed article creation trial].'' Wikimedia, 2017. ;Examples of not-so-well documented open research projects * Eclarke. [https://github.com/eclarke/swga_paper SWGA paper]. GitHub, 2016. * David Lefevre. [https://figshare.com/articles/Lefevre_and_Cox_Delayed_instructional_feedback_may_be_more_effective_but_is_this_contrary_to_learners_preferences_/2061303 ''Lefevre and Cox: Delayed instructional feedback may be more effective, but is this contrary to learners’ preferences?''] Figshare, 2016. * Alneberg. [https://github.com/BinPro/paper-data ''CONCOCT Paper Data'']. GitHub, 2014. ;Other resources * Press, Gil. [https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#2608257f6f63 ''Cleaning Big Data: Most Time-Consuming, Least Enjoyable Data Science Task, Survey Says.''] Forbes, 2016. * Christensen, Garret. [https://github.com/garretchristensen/BestPracticesManual/blob/master/Manual.pdf ''Manual of Best Practices in Transparent Social Science Research.''] 2016. * Hickey, Walt. [https://fivethirtyeight.com/features/the-bechdel-test-checking-our-work/ ''The Bechdel Test: Checking Our Work'']. FiveThirtyEight, 2014. * Chapman et al. [ftp://ftp.software.ibm.com/software/analytics/spss/support/Modeler/Documentation/14/UserManual/CRISP-DM.pdf ''Cross Industry Standard Process for Data Mining'']. IBM, 2000. <br/> <hr/> <br/> === Week 4: October 18 === [[HCDS_(Fall_2018)/Day_4_plan|Day 4 plan]] <!-- [[:File:HCDS Week 4 slides.pdf|Day 4 slides]] --> ;Interrogating datasets: ''bias in data; best practices for selecting, describing, and implementing training data'' ;Assignments due * Reading reflection * A1: Data curation ;Agenda {{:HCDS (Fall 2018)/Day 4 plan}} ;Readings assigned * Read: Duarte, N., Llanso, E., & Loup, A. (2018). Mixed Messages? The Limits of Automated Social Media Content Analysis. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 81, 106. PDF: http://proceedings.mlr.press/v81/duarte18a.html * Read: Bender, E. M., & Friedman, B. (2018). Data Statements for NLP: Toward Mitigating System Bias and Enabling Better Science. T0 appear in Transactions of the ACL. PDF: https://openreview.net/forum?id=By4oPeX9f ;Homework assigned * Reading reflection * A2: Bias in data ;Resources * Aschwanden, Christie. [https://fivethirtyeight.com/features/science-isnt-broken/ ''Science Isn't Broken''] FiveThirtyEight, 2015. * Shyong (Tony) K. Lam, Anuradha Uduwage, Zhenhua Dong, Shilad Sen, David R. Musicant, Loren Terveen, and John Riedl. 2011. ''[http://files.grouplens.org/papers/wp-gender-wikisym2011.pdf WP:clubhouse?: an exploration of Wikipedia's gender imbalance.]'' In Proceedings of the 7th International Symposium on Wikis and Open Collaboration (WikiSym '11). ACM, New York, NY, USA, 1-10. DOI=http://dx.doi.org/10.1145/2038558.2038560 * Shilad Sen, Margaret E. Giesel, Rebecca Gold, Benjamin Hillmann, Matt Lesicko, Samuel Naden, Jesse Russell, Zixiao (Ken) Wang, and Brent Hecht. 2015. ''[http://www-users.cs.umn.edu/~bhecht/publications/goldstandards_CSCW2015.pdf Turkers, Scholars, "Arafat" and "Peace": Cultural Communities and Algorithmic Gold Standards]''. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '15). DOI: http://dx.doi.org/10.1145/2675133.2675285 <br/> <hr/> <br/> === Week 5: October 25 === [[HCDS_(Fall_2018)/Day_5_plan|Day 5 plan]] <!-- [[:File:HCDS Week 5 slides.pdf|Day 5 slides]] --> ;Introduction to mixed-methods research: ''Big data vs thick data; integrating qualitative research methods into data science practice'' ;Assignments due * Reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 5 plan}} ;Readings assigned * R. Stuart Geiger and Aaron Halfaker. 2017. ''[https://commons.wikimedia.org/wiki/File:conflict-bots-wp-cscw.pdf Operationalizing conflict and cooperation between automated software agents in Wikipedia: A replication and expansion of Even Good Bots Fight]''. Proceedings of the ACM on Human-Computer Interaction (Nov 2017 issue, CSCW 2018 Online First) 1, 2, Article 49. DOI: https://doi.org/10.1145/3134684 ;Homework assigned * Reading reflection * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A3:_Crowdwork_ethnography|A3: Crowdwork ethnography]] ;Resources * WeArDynamo contributors. ''[http://wiki.wearedynamo.org/index.php?title=Basics_of_how_to_be_a_good_requester How to be a good requester]'' and ''[http://wiki.wearedynamo.org/index.php?title=Guidelines_for_Academic_Requesters Guidelines for Academic Requesters]''. Wearedynamo.org * Wang, Tricia. ''[https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7 Why Big Data Needs Thick Data]''. Ethnography Matters, 2016. * Maximillian Klein. ''[http://whgi.wmflabs.org/gender-by-language.html Gender by Wikipedia Language]''. Wikidata Human Gender Indicators (WHGI), 2017. * Benjamin Collier and Julia Bear. ''[https://static1.squarespace.com/static/521c8817e4b0dca2590b4591/t/523745abe4b05150ff027a6e/1379354027662/2012+-+Collier%2C+Bear+-+Conflict%2C+confidence%2C+or+criticism+an+empirical+examination+of+the+gender+gap+in+Wikipedia.pdf Conflict, criticism, or confidence: an empirical examination of the gender gap in wikipedia contributions]''. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work (CSCW '12). DOI: https://doi.org/10.1145/2145204.2145265 * Christina Shane-Simpson, Kristen Gillespie-Lynch, Examining potential mechanisms underlying the Wikipedia gender gap through a collaborative editing task, In Computers in Human Behavior, Volume 66, 2017, https://doi.org/10.1016/j.chb.2016.09.043. (PDF on Canvas) * Amanda Menking and Ingrid Erickson. 2015. ''[https://upload.wikimedia.org/wikipedia/commons/7/77/The_Heart_Work_of_Wikipedia_Gendered,_Emotional_Labor_in_the_World%27s_Largest_Online_Encyclopedia.pdf The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia]''. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). https://doi.org/10.1145/2702123.2702514 * Kevin Crowston and the Gravity Spy Team. 2017. ''[https://crowston.syr.edu/sites/crowston.syr.edu/files/cpa137-crowstonA.pdf Gravity Spy: Humans, Machines and The Future of Citizen Science].'' In Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17 Companion). ACM, New York, NY, USA, 163-166. DOI: https://doi.org/10.1145/3022198.3026329 <br/> <hr/> <br/> === Week 6: November 1 === [[HCDS_(Fall_2018)/Day_6_plan|Day 6 plan]] <!-- [[:File:HCDS Week 6 slides.pdf|Day 6 slides]] --> ;Interrogating algorithms: ''algorithmic fairness, transparency, and accountability; methods and contexts for algorithmic audits'' ;Assignments due * Reading reflection * A2: Bias in data ;Agenda {{:HCDS (Fall 2018)/Day 6 plan}} ;Readings assigned * Read: Christian Sandvig, Kevin Hamilton, Karrie Karahalios, Cedric Langbort (2014/05/22) ''[http://www-personal.umich.edu/~csandvig/research/Auditing%20Algorithms%20--%20Sandvig%20--%20ICA%202014%20Data%20and%20Discrimination%20Preconference.pdf Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms].'' Paper presented to "Data and Discrimination: Converting Critical Concerns into Productive Inquiry," a preconference at the 64th Annual Meeting of the International Communication Association. May 22, 2014; Seattle, WA, USA. * Read: Diakopoulos, N. (2014). Algorithmic accountability reporting: On the investigation of black boxes. Tow Center for Digital Journalism, 1–33. https://doi.org/10.1002/ejoc.201200111 ;Homework assigned * Reading reflection ;Resources * Hill, Kashmir. ''[https://gizmodo.com/facebook-figured-out-my-family-secrets-and-it-wont-tel-1797696163 Facebook figured out my family secrets, and it won't tell me how].'' Engadget, 2017. * Blue, Violet. ''[https://www.engadget.com/2017/09/01/google-perspective-comment-ranking-system/ Google’s comment-ranking system will be a hit with the alt-right].'' Engadget, 2017. * Ingold, David and Soper, Spencer. ''[https://www.bloomberg.com/graphics/2016-amazon-same-day/ Amazon Doesn’t Consider the Race of Its Customers. Should It?].'' Bloomberg, 2016. * Paul Lamere. ''[https://musicmachinery.com/2011/05/14/how-good-is-googles-instant-mix/ How good is Google's Instant Mix?].'' Music Machinery, 2011. * Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner. ''[https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias: Risk Assessment in Criminal Sentencing]. Propublica, May 2018. <!-- * Mars, Roman. ''[https://99percentinvisible.org/episode/the-age-of-the-algorithm/ The Age of the Algorithm].'' 99% Invisible Podcast, 2017. * [https://www.perspectiveapi.com/#/ Google's Perspective API] --> <br/> <hr/> <br/> === Week 7: November 8 === [[HCDS_(Fall_2018)/Day_7_plan|Day 7 plan]] ;Critical approaches to data science: ''power, data, and society; ethics of crowdwork'' ;Assignments due * Reading reflection * A3: Crowdwork ethnography ;Agenda {{:HCDS (Fall 2018)/Day 7 plan}} ;Readings assigned (read both, reflect on one) * TBD ;Homework assigned * Reading reflection * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A4:_Final_project_plan|A4: Final project plan]] ;Resources * Neff, G., Tanweer, A., Fiore-Gartland, B., & Osburn, L. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science. Big Data, 5(2), 85–97. https://doi.org/10.1089/big.2016.0050 * Lilly C. Irani and M. Six Silberman. 2013. ''[https://escholarship.org/content/qt10c125z3/qt10c125z3.pdf Turkopticon: interrupting worker invisibility in amazon mechanical turk]''. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). DOI: https://doi.org/10.1145/2470654.2470742 * Bivens, R. and Haimson, O.L. 2016. ''[http://journals.sagepub.com/doi/pdf/10.1177/2056305116672486 Baking Gender Into Social Media Design: How Platforms Shape Categories for Users and Advertisers]''. Social Media + Society. 2, 4 (2016), 205630511667248. DOI:https://doi.org/10.1177/2056305116672486. * Schlesinger, A. et al. 2017. ''[http://arischlesinger.com/wp-content/uploads/2017/03/chi2017-schlesinger-intersectionality.pdf Intersectional HCI: Engaging Identity through Gender, Race, and Class].'' Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17. (2017), 5412–5427. DOI:https://doi.org/10.1145/3025453.3025766. <br/> <hr/> <br/> === Week 8: November 15 === [[HCDS_(Fall_2018)/Day_8_plan|Day 8 plan]] <!-- [[:File:HCDS Week 8 slides.pdf|Day 8 slides]] --> ;Human-centered algorithm design: ''algorithmic interpretibility; human-centered methods for designing and evaluating algorithmic systems'' ;Assignments due * Reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 8 plan}} ;Readings assigned * Read: Baumer, E. P. S. (2017). Toward human-centered algorithm design. Big Data & Society, 4(2), 2053951717718854. https://doi.org/10.1177/2053951717718854 * Read: Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014). Power to the People: The Role of Humans in Interactive Machine Learning. AI Magazine, 35(4), 105. https://doi.org/10.1609/aimag.v35i4.2513 ;Homework assigned * Reading reflection ;Resources *Michael D. Ekstrand, F. Maxwell Harper, Martijn C. Willemsen, and Joseph A. Konstan. 2014. ''[https://md.ekstrandom.net/research/pubs/listcmp/listcmp.pdf User perception of differences in recommender algorithms].'' In Proceedings of the 8th ACM Conference on Recommender systems (RecSys '14). ACM, New York, NY, USA, 161-168. DOI: https://doi.org/10.1145/2645710.2645737 * Sean M. McNee, John Riedl, and Joseph A. Konstan. 2006. ''[http://files.grouplens.org/papers/mcnee-chi06-hri.pdf Making recommendations better: an analytic model for human-recommender interaction].'' In CHI '06 Extended Abstracts on Human Factors in Computing Systems (CHI EA '06). ACM, New York, NY, USA, 1103-1108. DOI=http://dx.doi.org/10.1145/1125451.1125660 * Sean M. McNee, Nishikant Kapoor, and Joseph A. Konstan. 2006. ''[http://files.grouplens.org/papers/p171-mcnee.pdf Don't look stupid: avoiding pitfalls when recommending research papers].'' In Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work (CSCW '06). ACM, New York, NY, USA, 171-180. DOI=http://dx.doi.org/10.1145/1180875.1180903 * Michael D. Ekstrand and Martijn C. Willemsen. 2016. ''[https://md.ekstrandom.net/research/pubs/behaviorism/BehaviorismIsNotEnough.pdf Behaviorism is Not Enough: Better Recommendations through Listening to Users].'' In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys '16). ACM, New York, NY, USA, 221-224. DOI: https://doi.org/10.1145/2959100.2959179 * Jess Holbrook. ''[https://medium.com/google-design/human-centered-machine-learning-a770d10562cd Human Centered Machine Learning].'' Google Design Blog. 2017. * Anderson, Carl. ''[https://medium.com/@leapingllamas/the-role-of-model-interpretability-in-data-science-703918f64330 The role of model interpretability in data science].'' Medium, 2016. <br/> <hr/> <br/> === Week 9: November 22 (No Class Session)=== [[HCDS_(Fall_2018)/Day_8_plan|Day 9 plan]] ;Data science for social good: ''Community-based and participatory approaches to data science; Using data science for society's benefit'' ;Assignments due * Reading reflection * A4: Final project plan ;Agenda {{:HCDS (Fall 2018)/Day 9 plan}} ;Readings assigned (Read and reflect on '''''one only''''') * Hill, B. M., Dailey, D., Guy, R. T., Lewis, B., Matsuzaki, M., & Morgan, J. T. (2017). Democratizing Data Science: The Community Data Science Workshops and Classes. In N. Jullien, S. A. Matei, & S. P. Goggins (Eds.), ''Big Data Factories: Scientific Collaborative approaches for virtual community data collection, repurposing, recombining, and dissemination''. New York, New York: Springer Nature. [[https://mako.cc/academic/hill_etal-cdsw_chapter-DRAFT.pdf Preprint/Draft PDF]] * Berney, Rachel, Bernease Herman, Gundula Proksch, Hillary Dawkins, Jacob Kovacs, Yahui Ma, Jacob Rich, and Amanda Tan. ''[https://dssg.uchicago.edu/wp-content/uploads/2017/09/berney.pdf Visualizing Equity: A Data Science for Social Good Tool and Model for Seattle].'' Data Science for Social Good Conference, September 2017, Chicago, Illinois USA (2017). ;Homework assigned * Reading reflection ;Resources * Daniela Aiello, Lisa Bates, et al. [https://shelterforce.org/2018/08/22/eviction-lab-misses-the-mark/ Eviction Lab Misses the Mark], ShelterForce, August 2018. <br/> <hr/> <br/> === Week 10: November 29 === [[HCDS_(Fall_2018)/Day_10_plan|Day 10 plan]] <!-- [[:File:HCDS Week 10 slides.pdf|Day 10 slides]] --> ;User experience and big data: ''Design considerations for machine learning applications; human centered data visualization; data storytelling'' ;Assignments due * Reading reflection ;Agenda {{:HCDS (Fall 2018)/Day 10 plan}} ;Readings assigned * Megan Risdal, ''[http://blog.kaggle.com/2016/06/29/communicating-data-science-a-guide-to-presenting-your-work/ Communicating data science: a guide to presenting your work].'' Kaggle blog, 2016. * Marilynn Larkin, ''[https://www.elsevier.com/connect/how-to-give-a-dynamic-scientific-presentation How to give a dynamic scientific presentation].'' Elsevier Connect, 2015. ;Homework assigned * Reading reflection * A5: Final presentation ;Resources * Bart P. Knijnenburg, Martijn C. Willemsen, Zeno Gantner, Hakan Soncu, and Chris Newell. 2012. ''[https://pure.tue.nl/ws/files/3484177/724656348730405.pdf Explaining the user experience of recommender systems].'' User Modeling and User-Adapted Interaction 22, 4-5 (October 2012), 441-504. DOI=http://dx.doi.org/10.1007/s11257-011-9118-4 * Megan Risdal, ''[http://blog.kaggle.com/2016/08/10/communicating-data-science-why-and-some-of-the-how-to-visualize-information/ Communicating data science: Why and how to visualize information].'' Kaggle blog, 2016. * Megan Risdal, ''[http://blog.kaggle.com/2016/06/13/communicating-data-science-an-interview-with-a-storytelling-expert-tyler-byers/ Communicating data science: an interview with a storytelling expert].'' Kaggle blog, 2016. * Richard Garber, ''[https://joyfulpublicspeaking.blogspot.com/2010/08/power-of-brief-speeches-world-war-i-and.html Power of brief speeches: World War I and the Four Minute Men].'' Joyful Public Speaking, 2010. * Brent Dykes, ''[https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ Data Storytelling: The Essential Data Science Skill Everyone Needs].'' Forbes, 2016. * Xavier Amatriain and Justin Basilico. ''[https://medium.com/netflix-techblog/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429 Netflix Recommendations: Beyond the 5 stars].'' Netflix Tech Blog, 2012. *Fabien Girardin. ''[https://medium.com/@girardin/experience-design-in-the-machine-learning-era-e16c87f4f2e2 Experience design in the machine learning era].'' Medium, 2016. * Chen, N., Brooks, M., Kocielnik, R., Hong, R., Smith, J., Lin, S., Qu, Z., Aragon, C. ''[https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1254&context=hicss-50 Lariat: A visual analytics tool for social media researchers to explore Twitter datasets].'' Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS), Data Analytics and Data Mining for Social Media Minitrack (2017) <br/> <hr/> <br/> === Week 11: December 6 === [[HCDS_(Fall_2018)/Day_11_plan|Day 11 plan]] ;Final presentations: course wrap up, presentation of student projects'' ;Assignments due * Reading reflection * A5: Final presentation ;Agenda {{:HCDS (Fall 2018)/Day 11 plan}} ;Readings assigned * none! ;Homework assigned * none! ;Resources * ''one'' <br/> <hr/> <br/> === Week 12: Finals Week (No Class Session) === * NO CLASS * A6: FINAL PROJECT REPORT DUE BY 11:59PM on Sunday, December 9 * LATE PROJECT SUBMISSIONS NOT ACCEPTED. [[Category:HCDS (Fall 2018)]]'
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