Data Driven Societies at Bowdoin College

This semester I am teaching Data Driven Societies as part of the new Digital and Computatial Studies Initiative at Bowdoin College. My co-instructor is the awesome Eric Gaze, Director of the Quantitative Reasoning Program and President of the National Numeracy Network. With 35 very excited students, we are where the social data sciences meet.

In the first week of class, students will select a hashtag on a social issue of their choice, and  scraping their hashtag data off of Twitter for at least a month. In labs, student will apply graph (Excel, R), spatial (GoogleMaps, Social Explorer), and network analysis (Gephi) skills learned in class to create data visualizations from their dataset and interpret the data. The readings we read in class will help them deal with some of the major issues framing issues of the web today, including Defining Data, Private(s), Public(s), The Life of Code, Sociality and Cyborgembodiment, and Power and Format. Quizzes will focus on key concepts learned in readings and labs, and the summary exam will include material from quizzes. The class concludes with students drafting a final paper from their blog posts and visuals into a summary analysis of the trends they see in their data.

As always, I welcome feedback and I’m eager to share with folks on similar paths. Data and society, onward!

Download a PDF of the syllabus here.

Interdisciplinary Studies 2420
Data Driven Societies || Spring 2014
Professor Eric Gaze & Professor Jack Jen Gieseking

Interpretation of the data changes based on the visual form it takes on. – Nathan Yau

Course Description

Big data and computational methods, such as changes in social media privacy laws and advances in mapping and network analysis, are changing financial markets, political campaigning, and higher education and becoming commonplace in our lives. Our daily existence is increasingly structured by code, from the algorithms that time our traffic lights to those that filter our search criteria and record our thoughts and ideas. In this course, we explore the possibilities, limitations, and implications of using digital and computational methods and analytics to study issues that affect our everyday lives from a social scientific approach. We pay special attention to the ways we collect, trust, analyze, portray, and use data, most especially the tools and meanings involved in data visualization and modeling.

This course tackles a number of cutting-edge issues and questions that confront society today: What sorts of questions can be asked and answered using digital and computational methods to rethink our relationships to data and what can data can show us about the world? How do we construct models to help us better understand social phenomena and associated data? What is data, and how do we know it’s reliable? How do these methods complement and sometimes challenge traditional methodologies in the social sciences? Students will leave the course with both substantive experience in digital and computational methods, Students will learn how to apply a critical lens for understanding and evaluating what computers can (and cannot) bring to the study of society.

Assignments

This class is a project-based, collaborative learning experience and experiment. For most of the semester there will be regular class readings for which you are responsible and a number of short assignments, including blog posts and comments, in-class quizzes, lab projects, and a hackathon. This will prepare you for the capstones of the course: an independent research paper and presentation, and an exam. Throughout the semester, time will be devoted to developing and implementing these projects in a series of scaffolded posts and quizzes as a process for you to set criteria for, build, and then evaluate your own project’s impact. Note: all blogs posts are due by 8 p.m. the day before class. Quiz and blog post/comment topics will be clarified in advance during class.

Evaluation Criteria
Labs                                                                      20%
Quizzes                                                                 15%
Blog posts and comments                                15%
Hackathon                                                            5%
Paper & presentation                                         35%
Exam                                                                     10%

Website, Textbooks, Texts, and Other Sources

You are required to acquire or make use of the following textbooks from ILL. The remainder of the texts are on e-reserve or can be found online.

Collaboration

All write-ups, reviews, documentation and other written material must be original and may not be derived from other sources. We plan on having a relaxed collaboration policy for this course. However, you should always be clear on what part of the work you hand in is your own, what parts come from other sources, and what parts are collaborative. Generally if you are exchanging information through a written, video, or visual medium then it rises to the level of something that you should report when you hand in your assignment. Exceptions would include getting help with a simple syntax error or where to find a certain button in a program. You will not be penalized for collaboration; it is just important for us to know to get a better sense of what you and your fellow students know. Failure to cite work that you draw from other sources is a violation of Bowdoin’s Academic Honor Code.

 

Class Breakdown

I. Defining Data though Data Collection, Access, Readability, and Reliability

A. Graph method and analysis

Mon 1/20        Digital and Computational Social Sciences: Introductions to Data

 

Wed 1/22        Social Data Sciences; or, Is everything “data” and is “everything” data?

Readings

Pentland, Alex. 2013. “The Data-Driven Society.” Scientific American 309 (4) (October 1): 78–83. doi:10.1038/scientificamerican1013-78.

Yau, Nathan. 2013. “Understanding Data.” In Data Points: Visualization That Means Something, 1–42. Hoboken, N.J.: Wiley.

Flip Classroom Assignments

Create a Twitter account

How to post to WordPress

How to set up your profile in WordPress

Install Python (for PC users)

Assignment: Blog post: why you chose your topic and what you expect to find.

 

Wed 1/22        LAB: Introduction to Data Scraping with Python & ScraperWiki

Readings

Yau, Nathan. 2011. “Handling Data.” In Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, 21–52. Indianapolis, Ind: Wiley.

 

Mon 1/27        How the Internet Works, from 1991 to Today

Readings

Berners-Lee, Tim, Robert Calliau, Ari Loutonen, Henrik Frystk Nielsen, and Arthur Secret. 1994. “The World Wide Web.” Communications of the ACM 37 (8): 76–82.

Marwick, Alice Emily. 2013. Excerpts from “A Cultural History of Web 2.0.” In Status Update: Celebrity, Publicity, and Branding in the Social Media Age, 21-35, 59–72. New Haven: Yale University Press.

Flip Classroom Assignment

Basics of Excel

 

Wed 1/29        How We Make Sense of Data in Visualization

Readings

Tufte, Edward R. 2011. “Visual & Statistical Thinking: Displays of Evidence for Making Decisions.” In Envisioning Information, 27–54. Cheshire, Conn.: Graphics Press.

Yau, Nathan. 2013. “Visualization: The Medium.” In Data Points: Visualization That Means Something, 43–90. Hoboken, N.J.: Wiley.

Assignments:

Quiz

Blog comment

 

Wed 1/29        LAB: Excel and statistics

 

Mon 2/3          Keeping it Real and Honest: Representing Data

Readings

Kurgan, Laura. 2013. “Representation and the Necessity of Interpretation.” In Close Up at a Distance: Mapping, Technology, and Politics, 19–38.

———. 2013. “Million-Dollar Blocks: The ‘Most Phenomenal’ Fact of All.” In Close Up at a Distance: Mapping, Technology, and Politics, 186–204.

Yau, Nathan. 2013. “Representing Data.” In Data Points: Visualization That Means Something, 91–134. Hoboken, N.J.: Wiley.

Projects to review:            

TBD

 

II. Private(s)

Wed 2/5          Privacy, Now: from the NSA to Facebook, Snapchat to Anonymous

Readings

Cohen, Julie E. 2012. “Introduction: Imagining the Networked Society.” In Configuring the Networked Self: Law, Code, and the Play of Everyday Practice, 3–31. New Haven: Yale University Press.

Illinsky, Noah P.N. 2010. “On Beauty.” In Beautiful Visualization: Looking at Data through the Eyes of Experts, edited by Julie Steele and Noah P.N. Illinsky, 1–15. Beijing, China: O’Reilly.

Assignments:

Blog post: what is data and how does representation matter in regard to your dataset.

Quiz

 

Wed 2/5          LAB: Using R to create histograms, pie charts, and line graphs

Readings

Yau, Nathan. 2011. “Visualizing Patterns over Time.” In Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, 91–134. Indianapolis, Ind: Wiley.

 

Mon 2/10        Defining “Big Data” and Redefining Privacy

Readings

boyd, danah, and Kate Crawford. 2012. “Critical Questions for Big Data.” Information, Communication & Society 15 (5): 662–679. doi:10.1080/1369118X.2012.678878.

Crawford, Kate. 2013. “Think Again: Big Data.” Foreign Policy, May 9.

Vis, Farida. 2013. “A Critical Reflection on Big Data: Considering APIs, Researchers and Tools as Data Makers.” First Monday 18 (10) (October 7). doi:http://dx.doi.org/10.5210%2Ffm.v18i10.4878. http://journals.uic.edu/ojs/index.php/fm/article/view/4878.

 

Wed 2/12        The Search Engine and the Search for Privacy

Readings

Pariser, Eli. 2012. “Introduction.” In The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think, 1–20. New York, N.Y.: Penguin Books/Penguin Press.

———. 2012. “The Race for Relevance.” In The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think, 21–46. New York, N.Y.: Penguin Books/Penguin Press.

Stray, Jonathan. 2012. “Are We Stuck in Filter Bubbles? Here Are Five Potential Paths Out.” Nieman Journalism Lab. July 11. http://www.niemanlab.org/2012/07/are-we-stuck-in-filter-bubbles-here-are-five-potential-paths-out/.

Assignment: Quiz

 

Wed 2/12        LAB: Using R for Correlation and Causation

Readings

Yau, Nathan. 2011. “Visualizing Relationships.” In Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, 179–226. Indianapolis, Ind: Wiley.

 

III. Public(s)

Mon 2/17        On Digital Publics of Opening…or Not

Readings

Donovan, Gregory. 2014. “Opening Proprietary Ecologies: Participatory Action Design Research with Young People.” In Methodological Challenges When Exploring Digital Learning Spaces in Education, edited by K.B. Vasbø and G.B. Gudmundsdottir. New York: Sense.

Odewahn, Andrew. 2010. “Visualizing the US Senate Social Graph (1991-2009).” In Beautiful Visualization: Looking at Data through the Eyes of Experts, edited by Julie Steele and Noah P.N. Illinsky, 123–142. Beijing, China: O’Reilly.

Golbeck, Jennifer. 2013. “Introduction; Nodes, Edges, and Network Measures.” In Analyzing the Social Web, 1–8, 9–24. Waltham, MA: Morgan Kaufmann/Elsevier.

Assignment: Blog comment

Projects to review:            

CartoDB. 2014. “Beyonce Releases Her New Album Online.” Beyonce Releases Her New Album Online: Geotagged Tweets Mentioning Beyonce’s Online Self-titled Album, December 12-13, 2013. Accessed January 8. http://srogers.cartodb.com/viz/337d9194-6458-11e3-85b5-e5e70547d141/embed_map?title=true&description=true&search=false&shareable=false&cartodb_logo=false&layer_selector=false&legends=false&scrollwheel=true&sublayer_options=.

Fraas, Mitch. 2013. “Mapping Books: The Dispersal of the Medieval Libraries of Great Britain”. Blog. Mapping Books. http://mappingbooks.blogspot.com/2013/11/the-dispersal-of-medieval-libraries-of.html.

 

Wed 2/19        Redefining Publics through Data

Readings    

Johnson, Jeffrey Alan. 2013. “From Open Data to Information Justice”. SSRN Scholarly Paper ID 2241092. Rochester, NY: Social Science Research Network. http://papers.ssrn.com/abstract=2241092.

Silver, Nate. 2012. Selections from The Signal and the Noise: Why So Many Predictions Fail — but Some Don’t. New York: Penguin Press HC, The.

Assignment: Quiz

 

Wed 2/19        LAB: Using R for Bayesian statistics

Readings

TBD

 

Mon 2/24        Public (Invisible) Labor

Readings

Irani, Lilly. 2012. “Microworking the Crowd.” Limn 2. http://limn.it/microworking-the-crowd/.

Ross, Andrew. 2013. “In Search of the Lost Paycheck.” In Digital Labor: The Internet as Playground and Factory, edited by Trebor Scholz, 13–32. Digital Labor: Routledge.

Golbeck, Jennifer. 2013. “Network Structure and Measures.” In Analyzing the Social Web, 25–44. Waltham, MA: Morgan Kaufmann/Elsevier.

Assignment: Blog post: reflect on your work in lab to turn your Twitter dataset

 

Wed 2/26        Convincing the Public / Publics Convincing Themselves

Readings

Baym, Nancy K., and danah boyd. 2012. “Socially Mediated Publicness: An Introduction.” Journal of Broadcasting & Electronic Media 56 (3): 320–329. doi:10.1080/08838151.2012.705200.

Lee, Newton. 2013. “Consumer Privacy in the Age of Big Data.” In Facebook Nation, 61–66. Springer New York.

Yau, Nathan. 2013. Selections from “Exploring Data Visually.” In Data Points: Visualization That Means Something, 135–153. Hoboken, N.J.: Wiley.

Golbeck, Jennifer. 2013. “Network Visualization.” In Analyzing the Social Web, 45–62. Waltham, MA: Morgan Kaufmann/Elsevier.

Assignment: Quiz

 

B. Spatial Analysis

Wed 2/26        LAB: Introduction to Google maps & Social Explorer

 

IV. The Life of Code

Mon 3/3          Code Is…

Readings

Grossman, Lev, Jay Newton-Small, Jessica Roy, and Laura Stampler. 2013. “The Deep Web.” Time 182 (20) (November 11): 26-33.

Lessig, Lawrence. 2006. “Code Is Law.” In Code: Version 2.0, 1–8. New York: Basic Books.

———. 2006. “Regulating Code.” In Code: Version 2.0, 61–80. New York: Basic Books.

Yau, Nathan. 2013. Selections from “Exploring Data Visually.” In Data Points: Visualization That Means Something, 176-200. Hoboken, N.J.: Wiley.

Assignment: Quiz

 

Wed 3/5          Seeing Code in Space and Place

Readings

Graham, Stephen D. N. 2005. “Software-Sorted Geographies.” Progress in Human Geography 29 (5) (October 1): 562–580. doi:10.1191/0309132505ph568oa.

Jabbour, Eddie, and Julie Steele. 2010. “Mapping Information: Redesigning the New York City Subway Map.” In Beautiful Visualization: Looking at Data through the Eyes of Experts, edited by Julie Steele and Noah P.N. Illinsky, 69–90. Beijing, China: O’Reilly.

Shanley, Lea, Ryan Burns, Zachary Bastian, and Edward S. Robson. 2013. “Tweeting Up a Storm: The Promise and Perils of Crisis Mapping.” Photogrammetric Engineering & Remote Sensing (October): 866–880.

Projects to review:

Rahul. 2013. “Occupy Sandy and Emerging Forms of Social Organization.” Ashley Dawson. Accessed December 18. http://ashleydawson.info/2013/05/11/occupy-sandy-and-emerging-forms-of-social-organization/.

Occupy Sandy Spokes Council. 2012. “Occupy Sandy Recovery.” Occupy Sandy Recovery. http://occupysandy.net/.

 

Wed 3/5          LAB: Examining Your Own Data with GoogleMaps and Social Explorer

 

Mon 3/7-23     Spring Break: No Classes or Labs

 

Mon 3/31        Code Undone

Readings

Coleman, Gabriella. 2012. “Am I Anonymous?” Limn (2). http://limn.it/am-i-anonymous/.

Wark, McKenzie. 2013. “Considerations on a Hacker Manifesto.” In Digital Labor: The Internet as Playground and Factory, edited by Trebor Scholz, 69–76. Digital Labor: Routledge.

Golbeck, Jennifer. 2013. “Tie Strength.” In Analyzing the Social Web, 63–74. Waltham, MA: Morgan Kaufmann/Elsevier.

Projects to review:

Baldwin, J.R. 2012. “Top Needs of Occupy Sites | Limn.” Limn 2. http://limn.it/top-needs-of-occupy-sites/.

 

Wed 4/2          Whose Code? Whose Culture?

Readings

Kitchin, Rob, and Martin Dodge. 2014. “Introducing Code/Space.” In Code/Space: Software and Everyday Life, 3–22. Cambridge, MA: MIT Press.

Donovan, Gregory, and Cindi Katz. 2009. “Cookie Monsters: Seeing Young People’s Hacking as Creative Practice.” Children, Youth and Environments 19 (1): 197–222.

Assignments:

Quiz

Blog post: speak to your GoogleMaps and Social Explorer maps related to your datasets.

 

Wed 4/2          LAB: Using Excel and R with Your Data

 

V. Sociality & Cyborgembodiment

Mon 4/7          Our Bodies, Our(Social Media)selves: Cyborg Embodiment

Readings

Nakamura, Lisa. 2010. “Race and Identity in Digital Media.” In Mass Media and Society, edited by James Curran, 336–347. New York: Bloomsbury.

Neff, Gina. 2013. “Why Big Data Won’t Cure Us.” Big Data 1 (3) (September): 117–123. doi:10.1089/big.2013.0029.

Yau, Nathan. 2013. Selections from “Visualizing with Clarity.” In Data Points: Visualization That Means Something, 201–220. Hoboken, N.J.: Wiley.

Golbeck, Jennifer. 2013. “Trust.” In Analyzing the Social Web, 75–90. Waltham, MA: Morgan Kaufmann/Elsevier.

Projects to review: TBD

 

C. Network Analysis

Wed 4/9          Professors Gieseking and Gaze will be at conferences – read/lab on your own

Readings

Golbeck, Jennifer. 2013. “Understanding Structure through User Attributes and Behavior.” In Analyzing the Social Web, 91–106. Waltham, MA: Morgan Kaufmann/Elsevier.

———. 2013. “Building Networks.” In Analyzing the Social Web, 107–124. Waltham, MA: Morgan Kaufmann/Elsevier.

Yau, Nathan. 2013. Selections from “Visualizing with Clarity.” In Data Points: Visualization That Means Something, 221–240. Hoboken, N.J.: Wiley.

Assignment: Blog post: write about the graphs that you created from your data in lab.

 

Wed 4/9          LAB: Gephi Quick Start Tutorial on Les Mis (on your own)

 

Mon 4/14        Identity Online

Readings

Gray, Mary L. 2007. “From Websites to Wal-Mart: Youth, Identity Work, and the Queering of Boundary Publics in Small Town, USA.” American Studies 48 (2) (July 1): 49–59.

Nakamura, Lisa. 2011. “Syrian Lesbian Bloggers, Fake Geishas, and the Attractions of Identity Tourism” Hyphen: Asian America Unabridged (July 15). http://www.hyphenmagazine.com/blog/archive/2011/07/syrian-lesbian-bloggers-fake-geishas-and-attractions-identity-tourism.

Krebs, Valdis. 2010. “Your Choice Reveals Who You Are: Mining and Visualizing Social Patterns.” In Beautiful Visualization: Looking at Data through the Eyes of Experts, edited by Julie Steele and Noah P.N. Illinsky, 103–122. Beijing, China: O’Reilly.

Golbeck, Jennifer. 2013. “Building Networks.” In Analyzing the Social Web, 107–124. Waltham, MA: Morgan Kaufmann/Elsevier.

 

Wed 4/16        Creating Sociality, Producing New(s) Media

Readings

Miller, Greg. 2013. “Here’s How Memes Went Viral — In the 1800s.” Wired Science: MapLab. November 4. http://www.wired.com/wiredscience/2013/11/data-mining-viral-texts-1800s/.

Perer, Adam. 2010. “Finding Beautiful Insights in the Chaos of Social Network Visualizations.” In Beautiful Visualization: Looking at Data through the Eyes of Experts, edited by Julie Steele and Noah P.N. Illinsky, 157–174. Beijing, China: O’Reilly.

Golbeck, Jennifer. 2013. “Entity Resolution and Link Prediction.” In Analyzing the Social Web, 125–150. Waltham, MA: Morgan Kaufmann/Elsevier.

Golbeck, Jennifer. 2013. “Propagation in Networks.” In Analyzing the Social Web, 151–168. Waltham, MA: Morgan Kaufmann/Elsevier.

Flip Classroom Assignments

Netvizz your dataset from Facebook

Assignment: Quiz

 

Wed 4/16        LAB: Visualizing and Reading Your Own Facebook Social Network

 

VI. Power & Format

Mon 4/21        Remix

Readings

Lessig, Lawrence. 2009. “Cultures of Our Past.” In Remix: Making Art and Commerce Thrive in the Hybrid Economy, 23–33. New York: Penguin Books.

———. 2009. “Cultures of Our Future.” In Remix: Making Art and Commerce Thrive in the Hybrid Economy, 34–35. New York: Penguin Books.

———. 200c. “RO, Extended.” In Remix: Making Art and Commerce Thrive in the Hybrid Economy, 36–50. New York: Penguin Books.

———. 2009. “RW, Revived.” In Remix: Making Art and Commerce Thrive in the Hybrid Economy, 51–83. New York: Penguin Books.

Projects to review:

“DOCC 2013: Dialogues on Feminism and Technology | FemTechNet.” 2013. Accessed December 3. http://femtechnet.newschool.edu/docc2013/.

Assignment: Blog comment

 

Weds 4/23       Media Archaeology+

Readings

Anderson, Chris. 2012. “The Long Tail.” In The Social Media Reader, edited by Michael Mandiberg, 137–154. New York: New York University Press.

Sterne, Jonathan. 2006. “The MP3 as Cultural Artifact.” New Media & Society 8 (5) (October 1): 825–842. doi:10.1177/1461444806067737.

Assignment: Quiz

 

Wed 4/23        LAB: Build a Network Analysis from Your Twitter Data Set

 

Mon 4/28        Visualization as Power & Format

Readings

Davison, Patrick. 2012. “The Language of Internet Memes.” In The Social Media Reader, edited by Michael Mandiberg, 120–136. New York: New York University Press.

Hagy, Jessica. 2010. “Visualization: Indexed.” In Beautiful Visualization: Looking at Data through the Eyes of Experts, edited by Julie Steele and Noah P.N. Illinsky, 353–368. Beijing, China: O’Reilly.

Assignment: Blog comment

 

Weds 4/30       Spacetime to work on final projects

Readings

Yau, Nathan. 2013. “Designing for an Audience.” In Data Points: Visualization That Means Something, 241–276. Hoboken, N.J.: Wiley.

 

Wed 4/30        LAB: Spacetime to work on final projects

 

Mon 5/5          Final presentations

 

Wed 5/7          Final presentations

 

Wed 5/7          No lab

 

Mon 5/12        Papers due

 

Fri 5/17           Final exam at 9am