Social Computing

This course explores the intersection of social behavior and computational systems. The growth of online environments like Facebook, Wikipedia, Twitter, Instagram, WhatsApp, blogs, online support groups, open-source development projects, and crowdsourcing platforms shows that web technology is not just about delivering information, but also connecting people. Social Computing is the study of social processes and the technology that supports and augments it. Students will examine a range of organizational, technical, and business challenges related to social computing, and learn how to use tools to analyze, design, and build online communities. Social computing draws from fields as diverse as cognitive science, software engineering, artificial intelligence, sociology, anthropology, psychology, and organizational behavior. Course work will include lectures, class discussion, homework, class presentations, and a group research or design project.

  • Instructor: Prof. Steven Dow
  • TA: Srishti Palani
  • Fall 2019
  • T/Th 9:30-10:50am
  • Location: HSS 1346

Learning Objectives

Students will gain an overview of social computing applications and research topics. Students will read, discuss, and present key papers in the field. Each week, students will report on a social experience with a different type of technology.

Designing technologies for social interaction. Students will learn basic design skills for brainstorming, prototyping, and evaluating social technology. As part of a team project, students will prototype new social computing experiences during in-class studio time.

Measuring impact using online analytics. Students will learn about what impacts the spread of social artifacts and how to measure reach.

Course Activities

Lectures can be a bore. You learn more by teaching others and engaging through interactive activities. In this class, we expect you to actively participate in group projects, experience reports, in-class activities, and paper discussions. There will be no quizzes or exams. Major course activities include:

  • Experience reports: Every week reflect on a new experience with social computing
  • Paper presentations (teams of 2): Twice per quarter sign up to present a paper for the whole class
  • Online commenting: Every week read one paper in depth and write a discussion post
  • Midterm project (teams of 2-3 people): create and measure a novel meme for social media
  • Final project (teams of 4-5): design, build, and test your own social computing system
  • In-class activities
Syllabus for COGS 123 Social Computing (Fall 2019)

Course Topics

  • Online collaboration, awareness, coordination
  • Social data mining and analysis
  • Interaction design and research methods
  • Mobile web, urban computing
  • Online experimentation
  • Games, virtual communities
  • Crowdsourcing/human computation
  • Distributed innovation
  • Peer production systems
  • Citizen science, crisis informatics

Course Origins

This course draws on reading lists and syllabi from many institutions. The most direct inspiration comes from the Social Web course taught at CMU by Jeffrey Bigham, Robert Kraut, Jason Hong, and Niki Kittur. It also combines aspects of Social Computing and Online Communities by Eric Gilbert and Amy Bruckman, Social Spaces on the Internet by Karrie Karahalios, Social Computing Systems by Walter Lasecki, Social Computing by Leysia Palen, Social Computing by Juho Kim, and Computer-Supported Cooperative Work by Gary Olson, Katie Pine, and many others. Feel free to explore these course syllabi for additional material and papers.

Instructor

Steven Dow is Associate Professor of Cognitive Science at UC San Diego where he researches human-computer interaction, social computing, and creativity. Steven received the National Science Foundation CAREER Award in 2015 for research on "advancing collective innovation." He was co-PI on four other National Science Foundation grants, a Google Faculty Grant, Stanford's Postdoctoral Research Award, and the Hasso Plattner Design Thinking Research Grant. Before UCSD, Steven was an Assistant Professor of Human-Computer Interaction at Carnegie Mellon University. He holds an MS and PhD in Human-Centered Computing from the Georgia Institute of Technology, and a BS in Industrial Engineering from University of Iowa.

Teaching Assistant

Srishti Palani is a second-year Cognitive Science PhD student excited about research in Human Computer Interaction. Through her research at the Design Lab, she designs systems that empower everyone to be more creative. In 2018, she graduated summa cum laude in Computer Science and Psychology from Mount Holyoke College. When she’s not researching, you can find her playing squash, learning to surf, or petting dogs.

Archive of Class Projects