This course focuses on how social groups form and evolve, how members of these groups interact with each other, and how these groups are supported and augmented with computer systems and technology. The course is interdisciplinary, drawing from the fields of Computing and Information as well as Humanities, and Social Sciences. It covers key theories and technologies of social computing in terms of (1) computer systems supporting social behavior and (2) socially intelligent computing carried out by groups. Students will have a chance to explore social computing systems, get experience with social data analyses and focus on design, and evaluation of a social software as their final project for the course. The course follows a very hands-on format and include in-class activities that are integrated within each lecture. Students' participation in the classes and activities play an important role in their learning of the courses materials; therefore, they are highly encouraged not to miss classes.


This course does not assume any particular prerequisites. However, this is a graduate course which assumes critical thinking, desire to learn and being challenged with new topics, and hard work.


We will be reading excerpts from a large number of books and articles. Links to electronic copies are provided.



Email or online meetings by appointment:



12023-08-30Introduction and overviewCourse logistics and requirements
Overview of what social computing is about and what you will learn in this course
22023-09-06Social softwareWhat is social software?
Connecting people through technology
Open source software development
32023-09-13Virtual WorldsDesigning virtual worlds
Virtual identity
Reading assignment 1: in-class presentation
42023-09-20Team communicationTeam communication
Computer supported collaboration tools
Content sharing
Team communication in virutal worlds
Project ideas due
52023-09-27Project topic and team formation Instructor will provide feedback for each team on the general idea, methods, and plan of their project
62023-10-04Social Networks and Social Network AnalysisNetworks: definition, metrics
Social networks: Design, Technology, Features, and Impacts
Social networks analysis: Why and How
72023-10-11Social data analysisVisualization and sense-making of social data
Social and collaborative exploration of data
Collecting social traces
Social media APIs
82023-10-18Work timeWork with your groups on your projects and data analysis assignment
Quiz 1: Network analysis and virtual worlds
92023-10-25Project progress reportIn-class presentation of developed project idea, progress report, and feedback on your projects
102023-11-01Social computing theoriesTheories of personal behavior
Theories of social behavior
Mass communication theories
112023-11-08Social capitalDefinitions and measures
Social capital and social networks
Role of online communities on social capital
122023-11-15Socially intelligent computingCollective intelligence
Content based recommender systems
Collaborative filtering recommender systems
Quiz 2: Social computing theories
132023-11-22No classThanksgiving break
142023-11-29Social information processingSocial navigation
Social search
Social bots
Social data analysis assignment due
152023-12-06Social computing: ethics and societal impactImpact on physical and psychological well-being
Interplay of online and offline world
Social media ethics
162023-12-13Final projectFinal project presentations and report


Academic Integrity: You are expected to be fully aware of your responsibility to maintain a high quality of integrity in all of your work. All work must be your own, unless collaboration is specifically and explicitly permitted as in the course group project. Any unauthorized collaboration or copying will at minimum result in no credit for the affected assignment and may be subject to further action under the University Guidelines for Academic Integrity. You are expected to have read and understood these Guidelines. A document discussing these guidelines was included in your orientation materials.

Attendance: Class attendance, while not mandatory, is required if you want to succeed in this course, especially since the course does not have any course book and involves a lot of in-class discussions. If you have missed the lecture, make sure that you have a copy of the slides. All the lecture materials will be uploaded online. The in-class activities are engineered to encourage your attendance.

Late Submissions: Every student has a total of 3 days late-submission quota to use on your assignments; i.e. you can submit one assignment 3 days late and you will be ok, or you can submit 3 assignment each 1 day late and you will be ok. Late submission cannot be accepted for assignments that require in-class presentation

Concerning Students with Disabilities: If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your instructor and Disability Resources and Services, 216 William Pitt Union, (412) 648-7890/(412) 383-7355 (TTY), as early as possible in the term. DRS will verify your disability and determine reasonable accommodations for this course.

An important note on plagiarism: Cheating and plagiarism will not be tolerated. Students caught cheating or plagiarizing will receive no credit for the assignment on which the cheating occurred. Additional actions -- including assigning the student a failing grade in the class or referring the case for disciplinary action -- may be taken at the discretion of the instructors. You may incorporate excerpts from publications by other authors, but they must be clearly marked as quotations and properly attributed. You may obtain copy editing assistance, and you may discuss your ideas with others, but all substantive writing and ideas must be your own or else be explicitly attributed to another, using a citation sufficiently detailed for someone else to easily locate your source.