Editing HCDS (Fall 2017)/Schedule

From CommunityData
Warning: You are not logged in. Your IP address will be publicly visible if you make any edits. If you log in or create an account, your edits will be attributed to your username, along with other benefits.

The edit can be undone. Please check the comparison below to verify that this is what you want to do, and then publish the changes below to finish undoing the edit.

Latest revision Your text
Line 1: Line 1:
<!--
<noinclude>
<noinclude>
<div style="font-family:Rockwell,'Courier Bold',Courier,Georgia,'Times New Roman',Times,serif; min-width:10em;">
<div style="font-family:Rockwell,'Courier Bold',Courier,Georgia,'Times New Roman',Times,serif; min-width:10em;">
Line 15: Line 14:
|bottom font-size= 1em
|bottom font-size= 1em
|bottom color= FFF
|bottom color= FFF
|bottom text=
|bottom text=Last updated on {{REVISIONMONTH:HCDS_(Fall_2017)}}/{{REVISIONDAY2:HCDS_(Fall_2017)}}/{{REVISIONYEAR:HCDS_(Fall_2017)}} by {{REVISIONUSER:HCDS_(Fall_2017)}}
|line= none
|line= none
}}</div></div>
}}</div></div>
</noinclude>
</noinclude>
-->


=== Week 1: September 28 ===
=== Week 1: September 28 ===
[[HCDS_(Fall_2017)/Day_1_plan|Day 1 plan]]
[[HCDS_(Fall_2017)/Day_1_plan|Day 1 plan]]
[[:File:HCDS Week 1 slides.pdf|Day 1 slides]]
;Course overview: ''What is data science? What is human centered? What is human centered data science?''


;Assignments due
;Assignments due
Line 56: Line 50:
[[HCDS_(Fall_2017)/Day_2_plan|Day 2 plan]]
[[HCDS_(Fall_2017)/Day_2_plan|Day 2 plan]]


[[:File:HCDS Week 2 slides.pdf|Day 2 slides]]
Ethical considerations in Data Science: privacy, informed consent and user treatment
 
;Ethical considerations in Data Science: ''privacy, informed consent and user treatment''




Line 88: Line 80:
* Hsu, Danny. [http://blog.datasift.com/2015/04/09/techniques-to-anonymize-human-data/ ''Techniques to Anonymize Human Data.''] Data Sift, 2015.
* 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.
* Metcalf, Jacob. [http://ethicalresolve.com/twelve-principles-of-data-ethics/ ''Twelve principles of data ethics'']. Ethical Resolve, 2016.
* Poor, Nathaniel and Davidson, Roei. [https://cscw2016hcds.files.wordpress.com/2015/10/poor_hcds20161.pdf ''When The Data You Want Comes From Hackers, Or, Looking A Gift Horse In The Mouth'']. CSCW Human Centered Data Science Workshop, 2016.
<br/>
<br/>
<hr/>
<hr/>
Line 95: Line 86:
=== Week 3: October 12 ===
=== Week 3: October 12 ===
[[HCDS_(Fall_2017)/Day_3_plan|Day 3 plan]]
[[HCDS_(Fall_2017)/Day_3_plan|Day 3 plan]]
[[:File:HCDS Week 3 slides.pdf|Day 3 slides]]


;Data provenance, preparation, and reproducibility: ''data curation, preservation, documentation, and archiving; best practices for open scientific research''
;Data provenance, preparation, and reproducibility: ''data curation, preservation, documentation, and archiving; best practices for open scientific research''
Line 107: Line 96:


;Readings assigned  
;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: (''sections TBD''): Christensen, Garret. [https://github.com/garretchristensen/BestPracticesManual/blob/master/Manual.pdf ''Manual of Best Practices in Transparent Social Science Research.''] 2016.
* 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.
*Read: Fiesler, Casey. [https://medium.com/@cfiesler/law-ethics-of-scraping-what-hiq-v-linkedin-could-mean-for-researchers-violating-tos-787bd3322540 ''Law & Ethics of Scraping: What HiQ v LinkedIn Could Mean for Researchers Violating TOS.''] Medium, 2017.


;Homework assigned
;Homework assigned
* Reading reflection
* Reading reflection
* [[HCDS_(Fall_2017)/Assignments#A1:_Data_curation|A1: Data curation]]
* A1: Data curation


;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.
* Thain, Nithum; Dixon, Lucas; and Wulczyn, Ellery. [https://figshare.com/articles/Wikipedia_Talk_Labels_Toxicity/4563973 ''Wikipedia Talk Labels: Toxicity'']. Figshare, 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.


;Examples of not-so-well documented open research projects
;Resources
* 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.
* 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.
* 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.


Line 138: Line 115:
=== Week 4: October 19 ===
=== Week 4: October 19 ===
[[HCDS_(Fall_2017)/Day_4_plan|Day 4 plan]]
[[HCDS_(Fall_2017)/Day_4_plan|Day 4 plan]]
[[:File:HCDS Week 4 slides.pdf|Day 4 slides]]


;Study design: ''understanding your data; framing research questions; planning your study''
;Study design: ''understanding your data; framing research questions; planning your study''
Line 146: Line 121:
;Assignments due
;Assignments due
* Reading reflection
* Reading reflection
* A1: Data curation
* A2: Data curation


;Agenda
;Agenda
Line 152: Line 127:


;Readings assigned
;Readings assigned
* 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


;Homework assigned
;Homework assigned
* Reading reflection
* Reading reflection
* A2: Bias in data
* A3: Measuring bias in data




;Resources
;Resources
* Aschwanden, Christie. [https://fivethirtyeight.com/features/science-isnt-broken/ ''Science Isn't Broken''] FiveThirtyEight, 2015.
* Aschwanden, Christie. [https://fivethirtyeight.com/features/science-isnt-broken/ ''Science Isn't Broken''] FiveThirtyEight, 2015.
* Halfaker, Aaron et al. ''[https://www-users.cs.umn.edu/~halfak/publications/The_Rise_and_Decline/ The Rise and Decline of an Open Collaboration Community: How Wikipedia's reaction to sudden popularity is causing its decline].'' American Behavioral Scientist, 2012.
* Warnke-Wang, Morten. ''[https://meta.wikimedia.org/wiki/Research:Autoconfirmed_article_creation_trial Autoconfirmed article creation trial].'' Wikimedia, 2017.
* ''[https://www.forbes.com/sites/hbsworkingknowledge/2015/01/20/wikipedia-or-encyclopaedia-britannica-which-has-more-bias/#1a68e6337d4a Wikipedia Or Encyclopædia Britannica: Which Has More Bias?]''. Forbes, 2015. Based on Greenstein, Shane, and Feng Zhu.''[http://www.hbs.edu/faculty/Publication%20Files/15-023_e044cf50-f621-4759-a827-e9a3bf8920c0.pdf Do Experts or Collective Intelligence Write with More Bias? Evidence from Encyclopædia Britannica and Wikipedia]''. Harvard Business School working paper.
<br/>
<br/>
<hr/>
<hr/>
Line 171: Line 141:
=== Week 5: October 26 ===
=== Week 5: October 26 ===
[[HCDS_(Fall_2017)/Day_5_plan|Day 5 plan]]
[[HCDS_(Fall_2017)/Day_5_plan|Day 5 plan]]
[[:File:HCDS Week 5 slides.pdf|Day 5 slides]]


;Machine learning: ''ethical AI, algorithmic transparency, societal implications of machine learning''
;Machine learning: ''ethical AI, algorithmic transparency, societal implications of machine learning''
Line 178: Line 146:
;Assignments due
;Assignments due
* Reading reflection
* Reading reflection
* A3: Bias in data


;Agenda
;Agenda
Line 183: Line 152:


;Readings assigned
;Readings assigned
* 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.


;Homework assigned
;Homework assigned
Line 191: Line 159:


;Resources
;Resources
* Bamman, David ''[https://cscw2016hcds.files.wordpress.com/2015/10/bamman_hcds.pdf Interpretability in Human-Centered Data Science].'' 2016 CSCW workshop on Human-Centered Data Science.
* 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.
* 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.
* 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/>
<br/>
Line 205: Line 166:
=== Week 6: November 2 ===
=== Week 6: November 2 ===
[[HCDS_(Fall_2017)/Day_6_plan|Day 6 plan]]
[[HCDS_(Fall_2017)/Day_6_plan|Day 6 plan]]
[[:File:HCDS Week 6 slides.pdf|Day 6 slides]]


;Mixed-methods research: ''Big data vs thick data; qualitative research in data science ''
;Mixed-methods research: ''Big data vs thick data; qualitative research in data science ''
Line 213: Line 172:
;Assignments due
;Assignments due
* Reading reflection
* Reading reflection
* A2: Bias in data




Line 221: Line 179:


;Readings assigned
;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
;Homework assigned
Line 228: Line 185:


;Resources
;Resources
* 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
* Andrea Forte, Nazanin Andalibi, and Rachel Greenstadt. ''[http://andreaforte.net/ForteCSCW17-Anonymity.pdf Privacy, Anonymity, and Perceived Risk in Open Collaboration: A Study of Tor Users and Wikipedians]''. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17). DOI: https://doi.org/10.1145/2998181.2998273


<br/>
<br/>
Line 246: Line 198:
;Assignments due
;Assignments due
* Reading reflection
* Reading reflection
* A3: Final project plan
* A5: Final project plan




Line 252: Line 204:
{{:HCDS (Fall 2017)/Day 7 plan}}
{{:HCDS (Fall 2017)/Day 7 plan}}


;Readings assigned (read both, reflect on one)
;Readings assigned
* 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
* 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


;Homework assigned
;Homework assigned
* Reading reflection
* Reading reflection
* A4: Crowdwork ethnography
* A6: Self-ethnography




;Resources
;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
*''go here''
* Wang, Tricia. ''[https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7 Why Big Data Needs Thick Data]''. Ethnography Matters, 2016.
<!-- * Wanda J. Orlikowski. 1992. ''[https://dspace.mit.edu/bitstream/handle/1721.1/2412/SWP-3428-27000158-CCSTR-134.pdf%3Bjsessionid%3D89CCB8F0923C0235DB2902AA40C25E28?sequence%3D1 Learning from Notes: organizational issues in groupware implementation]''. In Proceedings of the 1992 ACM conference on Computer-supported cooperative work (CSCW '92). DOI=http://dx.doi.org/10.1145/143457.143549 -->


<br/>
<br/>
Line 273: Line 221:
[[HCDS_(Fall_2017)/Day_8_plan|Day 8 plan]]
[[HCDS_(Fall_2017)/Day_8_plan|Day 8 plan]]


[[:File:HCDS Week 8 slides.pdf|Day 8 slides]]
;User experience and big data: ''prototyping and user testing; benchmarking and iterative evaluation; UI design for data science''
 
;User experience and big data: ''user-centered design and evaluation of recommender systems; UI design for data science, collaborative visual analytics''




Line 285: Line 231:


;Readings assigned
;Readings assigned
*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
* 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)


;Homework assigned
;Homework assigned
Line 293: Line 237:


;Resources
;Resources
* 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
* 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
* 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.
* 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.
* Brian Whitman. ''[https://notes.variogr.am/2012/12/11/how-music-recommendation-works-and-doesnt-work/ How music recommendation works - and doesn't work].'' Variogram, 2012.
* Paul Lamere. ''[https://musicmachinery.com/2011/05/14/how-good-is-googles-instant-mix/ How good is Google's Instant Mix?].'' Music Machinery, 2011.
* Snyder, Jaime. ''[https://cscw2016hcds.files.wordpress.com/2015/10/snyder_hcds20162.pdf Values in the Design of Visualizations].'' 2016 CSCW workshop on Human-Centered Data Science.


<br/>
<br/>
Line 314: Line 249:
;Assignments due
;Assignments due
* Reading reflection
* Reading reflection
* A4: Crowdwork ethnography
* A6: Crowdwork self-ethnography


;Agenda
;Agenda
Line 320: Line 255:


;Readings assigned
;Readings assigned
* 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]]
* 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.


;Homework assigned
;Homework assigned
Line 328: Line 260:


;Resources
;Resources
* 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).
* Sayamindu Dasgupta and Benjamin Mako Hill. ''[https://cscw2016hcds.files.wordpress.com/2015/10/dasgupta_hcds2016.pdf Learning With Data: Designing for Community Introspection and Exploration].'' Position paper for Developing a Research Agenda for Human-Centered Data Science (a CSCW 2016 workshop).


<br/>
<br/>
Line 337: Line 267:
=== Week 10: November 30 ===
=== Week 10: November 30 ===
[[HCDS_(Fall_2017)/Day_10_plan|Day 10 plan]]
[[HCDS_(Fall_2017)/Day_10_plan|Day 10 plan]]
[[:File:HCDS Week 10 slides.pdf|Day 10 slides]]


;Communicating methods, results, and implications: translating for non-data scientists ''
;Communicating methods, results, and implications: translating for non-data scientists ''
Line 351: Line 279:


;Readings assigned
;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
;Homework assigned
* Reading reflection
* Reading reflection
* A5: Final presentation
* A7: Final presentation


;Resources
;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
* ''one''
* 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
* 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.


<br/>
<br/>
Line 374: Line 294:
[[HCDS_(Fall_2017)/Day_11_plan|Day 11 plan]]
[[HCDS_(Fall_2017)/Day_11_plan|Day 11 plan]]


;Future of human centered data science: course wrap up, final presentations''
;Future of human centered data science: ''case studies from research, industry, and policy; final presentations''




;Assignments due
;Assignments due
* Reading reflection
* Reading reflection
* A5: Final presentation
* Final presentation




Line 400: Line 320:
=== Week 12: Finals Week ===
=== Week 12: Finals Week ===
* NO CLASS
* NO CLASS
* A6: FINAL PROJECT REPORT DUE BY 11:59PM on Sunday, December 10
* FINAL PROJECT REPORT DUE BY 11:59PM on Sunday, December 10
* LATE PROJECT SUBMISSIONS NOT ACCEPTED.
* LATE PROJECT SUBMISSIONS NOT ACCEPTED.




[[Category:HCDS (Fall 2017)]]
[[Category:HCDS (Fall 2017)]]
Please note that all contributions to CommunityData are considered to be released under the Attribution-Share Alike 3.0 Unported (see CommunityData:Copyrights for details). If you do not want your writing to be edited mercilessly and redistributed at will, then do not submit it here.
You are also promising us that you wrote this yourself, or copied it from a public domain or similar free resource. Do not submit copyrighted work without permission!

To protect the wiki against automated edit spam, we kindly ask you to solve the following CAPTCHA:

Cancel Editing help (opens in new window)