Course: CS 6474 Social Computing
Term: Fall 2016
Location: College of Computing 101
Time: Monday & Wednesday 4:35 – 5:55pm
Office Hours: By appointment
Teaching Assistant: Stevie Chancellor


This course is geared toward developing a broad understanding of the characteristics of today’s online social systems, including the opportunities and challenges that engender this emergent area. We will focus on the study of different social processes, behavior, and context on today's online social platforms, and learn how to make sense of the vast repositories of data that are generated on these platforms everyday. We will also learn about the design principles behind these systems and the key issues that arise from the widespread adoption of social computing systems in the wild. Learning objectives include:

- Collection and analysis of large-scale social data.
- Exploration of a variety of quantitative methodologies that could be applied to the study of social computing systems.
- Building social tools that augment current social computing systems.
- Apply social data to answer questions in a variety of practical scenarios and domains, spanning politics, economics, health.

The course will be taught seminar style, which means there will be weekly readings on a variety of topics (see topics and schedule below), and students will be required to participate in a group term project. There will be no exams, however there are going to be two assignments which will involve mini individual projects. Students will also be required to participate in discussions on the pre-assigned class readings in a blog, in order to demonstrate their understanding of the material, and to raise interesting questions and points for class discussion.

The term project will be 2-4 person group projects, and each group will be required to make a midterm presentation and a final presentation of their work. They will also need to submit a midterm report outlining their work as well as a final report. Each student will need to clearly articulate their concrete contribution in the group project. Topic of the project can be picked by the student groups after discussion with the instructor; the instructor will also provide a set of sample project ideas in class materials. If the project requires data analysis, a contribution of the project could be collecting that data, or the students could also use any of the publicly available social datasets available online. Each project will require both original work as well as a small number of compulsory analyses that cover key concepts from the course.

Students may audit the course, but all students who attend must perform the weekly blog posts about the reading, to facilitate discussion.

Required Skills: In terms of prerequisite skills, students need to have basic knowledge of statistics and preliminary machine learning. An overview of the concepts and tools needed will be reviewed across two lectures, however in-depth coverage of the fundamentals is not in the scope of this course. Students also need to be proficient in programming, in an object-oriented/scripting language (e.g., Python, Perl, C#). Experience in use of a scientific computing software like R is a bonus.

Academic Integrity: All assigned work is expected to be individual, except where explicitly indicated otherwise. You are encouraged to discuss the assignments with your classmates; however, what you hand in should be your own work. For more information, please review the Georgia Tech Honor Code.

Assignments and Grading

Responses to Class Readings (on Piazza; best 20) - 15%
Class Participation - 10%
Assignment I (due Oct 23, 11:59pm ET) - 15%
Assignment II (due Dec 13, 11:59pm ET) - 15%
Term Project - 45%
      : Project Proposal - 5%
      : Midterm Project Presentation - 5%
      : Midterm Report - 10%
      : Final Project Presentation - 5%
      : Final Report - 20%

Weekly Schedule *

Week 1 (22-Aug) Introduction
Week 1 (24-Aug) Background
Week 2 (29-Aug) Public Displays and Performance I (No in-class meeting)
Week 2 (31-Aug) Public Displays and Performance II
Week 3 (5-Sep) Labor Day - No Class
Week 3 (7-Sep) Disclosure and Regulation
Week 4 (12-Sep) Social Networking Sites
Classroom activity: bring laptops
Week 4 (14-Sep) Social Media Sites
Week 5 (19-Sep) Social Capital
Week 5 (21-Sep) Social Influence
Term Project Proposals Due
Week 6 (26-Sep) Quantitative Methods Review I
Week 6 (28-Sep) Quantitative Methods Review II
Week 7 (3-Oct) Social System Design
Classroom activity: bring laptops
Week 7 (5-Oct) Text Analytics I
Week 8 (10-Oct) Fall Recess - No Class
Week 8 (12-Oct) Text Analytics II
Week 9 (17-Oct) Deviant Communities
Week 9 (19-Oct) Network Structure I (No in-class meeting)
Week 10 (24-Oct) Network Structure II
Week 10 (26-Oct) Network Structure III
Week 11 (31-Oct) Trust
Week 11 (2-Nov) Midterm Project Presentations
Midterm Project Reports Due
Week 12 (7-Nov) Reputation, Social Signalling and Moderation
Week 12 (9-Nov) Credibility
Classroom activity: bring laptops
Week 13 (14-Nov) Polarization and Selective Exposure
Week 13 (16-Nov) News, Trends and Forecasting
Week 14 (21-Nov) Location and Mobility
Classroom activity: bring laptops
Week 14 (23-Nov) Thanksgiving Holiday - No Class
Week 15 (28-Nov) Activism and Social Movements
Week 15 (30-Nov) Privacy
Week 16 (5-Dec) TBA
Finals (12-Dec: 5:30-8pm; GVU Cafe)Final Project Presentations
Final Project Reports Due

Weekly Readings *

Week 2 (29-Aug): Public Displays and Performance I
The Presentation of Self in Everyday Life: Introduction (PDF file pgs. 6-10) [pdf]
The Presentation of Self in the Age of Social Media: Distinguishing Performances and Exhibitions Online [pdf]

Week 2 (31-Aug): Public Displays and Performance II
The Many Faces of Facebook: Experiencing Social Media as Performance, Exhibition, and Personal Archive [pdf]
Identity and Deception in the Virtual Community [pdf]

Week 3 (7-Sep): Disclosure and Regulation
Self-disclosure in Computer-Mediated Communication: The Role of Self-Awareness and Visual Anonymity [pdf]
4chan and/b: An Analysis of Anonymity and Ephemerality in a Large Online Community [pdf]

Week 4 (12-Sep): Social Networking Sites
Social Network Sites: Definition, History, and Scholarship [pdf]
Friendster and Publicly Articulated Social Networks [pdf]

Week 4 (14-Sep): Social Media Sites
Why We Twitter: Understanding Microblogging Usage and Communities [pdf]
Is It Really About Me?: Message Content in Social Awareness Streams [pdf]

Week 5 (19-Sep): Social Capital
The Benefits of Facebook “Friends:” Social Capital and College Students' Use of Online SNS [pdf]
Social Capital on Facebook: Differentiating Uses and Users [pdf]

Week 5 (21-Sep): Social Influence
Measuring User Influence in Twitter: The Million Follower Fallacy [pdf]
Everyone's an influencer: Quantifying Influence on Twitter [pdf]

Week 7 (3-Oct): Social System Design
Social Translucence: An Approach to Designing Systems that Support Social Processes [pdf]
The Chat Circles Series: Explorations in Designing Abstract Graphical Comm. Interfaces [pdf]

Week 7 (5-Oct): Text Analytics I
Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures [pdf]
Not All Moods Are Created Equal! Exploring Human Emotional States in Social Media [pdf]

Week 8 (12-Oct): Text Analytics II
Gender and Power: How Gender and Gender Environment Affect Manifestations of Power [pdf]
No Country for Old Members: User lifecycle and linguistic change in online communities [pdf]

Week 9 (17-Oct): Deviant Communities
Antisocial Behavior in Online Discussion Communities [pdf]
#thyghgapp: Instagram Content Moderation and Lexical Variation in Pro-Eating Disorder Communities [pdf]

Week 9 (19-Oct): Network Structure I
An Experimental Study of the Small World Problem [pdf]

Week 10 (24-Oct): Network Structure II
Structural Holes and Good Ideas [pdf]

Week 10 (26-Oct): Network Structure III
The Strength of Weak Ties [pdf]
Predicting Tie Strength With Social Media [pdf]

Week 11 (31-Oct): Trust
Trust Breaks Down in Electronic Contexts but Can Be Repaired by Some Initial F2F Contact [pdf]
Twitter Under Crisis: Can We Trust What We RT? [pdf]

Week 12 (7-Nov): Reputation, Social Signalling, and Moderation
Designing Reputation Systems for the Social Web [pdf]
Slash(dot) and Burn: Distributed Moderation in a Large Online Conversation Space [pdf]

Week 12 (9-Nov): Credibility
Tweeting is Believing? Understanding Microblog Credibility Perceptions [pdf]
Information Credibility on Twitter [pdf]

Week 13 (14-Nov): Polarization and Selective Exposure
Echo Chambers Online?: Politically Motivated Selective Exposure among Internet News Users [pdf]
Exposure to ideologically diverse news and opinion on Facebook [pdf]

Week 13 (16-Nov): News, Trends and Forecasting
Predicting the Future With Social Media [pdf]
Characterizing Debate Performance via Aggregated Twitter Sentiment [pdf]
What is Twitter, a Social Network or a News Media? [pdf]

Week 14 (21-Nov): Location and Mobility
Tweets from Justin Bieber's Heart: The Dynamics of the Location Field in User Profiles [pdf]
The Livehoods Project: Utilizing Social Media to Understand the Dynamics of a City [pdf]

Week 15 (28-Nov): Activism and Social Movements
The revolutions were tweeted: Information flows during the 2011 Tunisian and Egyptian revolutions [pdf]
Blogs as a Collective War Diary [pdf]

Week 15 (30-Nov): Privacy
Facebook, Youth and Privacy in Networked Publics [pdf]
"It's not that I don't have problems, I'm just not putting them on Facebook" [pdf]

Week 16 (5-Dec): To Be Assigned

Recommended, Relevant Readings

Not required, but the following books are good references for the class:

Networks, Crowds, and Markets, by David Easley and Jon Kleinberg
Six Degrees, by Duncan Watts
On Individuality and Social Forms, by Georg Simmel
Networked, by Barry Wellman
Writing for Social Scientists, by Howard Becker
Machine Learning for Hackers, by Drew Conway and John Myles White
Natural Language Processing with Python, by Steven Bird, Ewan Klein, and Edward Loper

* Topics to be covered and the corresponding readings are subject to change. Please always check the online schedule.