Social Computing
COGS 123 Social Computing (Fall 2024)
This course explores the intersection of social behavior and computational systems. The growth of online environments like Facebook, Wikipedia, Instagram, WhatsApp, TikTok, 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 prototype social computing experiences. 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 (Office Hours 12-1pm on Fridays on Zoom)
TAs: Lu Sun, Jeongeon Park, and Ivan Liang
IAs: Dia Bhalothia, Justine Dang, Rain Dong, Bianca Gao, Ian Gross, Wendy Hong, Arina Konnova, and AJ Sangle
Lectures on T/Th 11-12:20pm (Peterson 113)
Sections on Mondays (starts on Sept 30):
2pm: 679830 (CSB 003), 679833 (CSB 114/180), 679835 (CSB 272), 679838 (CSB 280)
3pm: 679839 (CSB 003), 680282 (CSB 114/180), 680931 (CSB 272), 680994 (CSB 280)
4pm: 681154 (CSB 003), 681182 (CSB 114/180), 681366 (CSB 272), 681916 (CSB 280)
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
This course includes readings, peer discussions, lectures and quizzes that cover the material for each week. In addition, students will actively participate in a group project to innovate and prototype novel social computing experiences. Course activities include:
Presentations: Present one paper per week within your section
Participation: Be active during open discussions in your discussion section and during lecture, and participate in activities
Quizzes: Demonstrate your understand of each week's material
Final project (teams of 4-5): Design, build, and test your own social computing experience
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. Initial 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 by Eric Gilbert, Online Communities and Amy Bruckman, Social Spaces on the Internet by Karrie Karahalios, Social Computing by Leysia Palen, Social Computing by Juho Kim, Social and Collaborative Computing by Amy Zhang, 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 (spdow@ucsd.edu) is a Professor of Cognitive Science at UC San Diego where he researches human-computer interaction, social computing, collective intelligence and creativity. Steven received the National Science Foundation CAREER Award in 2015 for research on "advancing collective innovation." He was co-PI on five other National Science Foundation grants, a Google Faculty Grant, Stanford's Postdoctoral Research Award, and the Hasso Plattner Design Thinking Research Grant. 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 Assistants
Lu Sun is a sixth year PhD candidate in Cognitive Science Department and the Design Lab. Her research area is Human Computer Interaction and Social Computing. She enjoys playing violin and tennis. She is excited to be a TA this year and she is looking forward to meeting everyone in this fascinating class!
Jeongeon Park is a first year Cognitive Science PhD student, working in Design Lab and ProtoLab. Her research interest is in Human-Computer Interaction, Human-AI Interaction, and Social Computing. She enjoys playing instruments, listening to music, and exploring nature. It is her first time TAing at UCSD, and she is excited to be meeting everyone with their wonderful ideas!
Ivan Liang is a second-year MS student in Computer Science Engineering and the Design Lab, with research interests in Human-Computer Interaction and Software Engineering. He looks forward to collaborating with everyone in COGS123. Outside of academia, Ivan enjoys coffee and traveling, and he’s excited to share this journey with you all.
Instructional Assistants
Dia Bhalothia, Justine Dang, Rain Dong, Bianca Gao, Ian Gross, Wendy Hong, Arina Konnova, and AJ Sangle