DESCRIPTION:
This course provides an introduction to the field of social computing. The course involves interdisciplinary topics, 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) computationals systems that shape and support social behavior and interactions and (2) socially intelligent computing carried out by groups. Students will have a chance to explore theories, methods, and tools used to analyze and design social computing systems, including social media, collaborative technologies, and online communities. The course emphasizes the bidirectional impact of technology on social processes and how social factors can influence the design and use of technology. The course follows a very interactive format and includes 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.
PREREQUISITES:
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.
TEXT:
We will be reading excerpts from a large number of books and articles. Links to electronic copies are provided.
GRADING:
- Participation activities [15 points]: Particiation during in-class activities
- Midterm exam [15 points]: Theoretical foundations
- Reading assignments [20 points]: the reading assignment is designed as paired assignment. You will read two papers for this assignment. For each paper, one student designs a set of 5 questions from the paper and the paired student answers those questions while reading the paper carefully. All students are required to read both papers carefully. During the class presentation, randomly selected team will present their questions and responses about the paper. The questions have to be conceptual and not too specific. Examples of good questions include: "What is the main problem the authors try to address in this paper?", "What approaches have the authors taken to address the problem?". Teams who present in the class will be awarded extra points
- Social data analysis assignment [15 points]: this is an individual assignment require you to analyze an existing social data to study a problem. The assignment will require you to use different data visualization and data storytelling to advocate for a change related to the problem you are studying.
- Final project [35 points]: The project involves design, prototyping, and evaluation of a social computing application related to a societal issues. It is a group project (groups of 3 or 4 students). Idea generation (5 points), Proposal (5 points), literature and system review (10 points), Final presentation and Final report (15 points)
OFFICE HOUR:
Email or online meetings by appointment:
- Instructor email: rfarzan at pitt dot edu
Learning Objectives:
- Understand key concepts and theories in social computing.
- Explore and criticise the design of different social computing technologies.
- Analyze social behavior in online environments.
- Examine the ethical implications of social computing technologies.
- Apply theories and methods in design of social computing technologies for real world problems.
SYLLABUS:
| # | Date | Topic | Details |
|---|---|---|---|
| 1 | 2024-08-28 | Introduction and Overview | Course logistics and requirements Overview of Social Computing, History, Evolution |
| 2 | 2024-09-04 | Theoretical foundations: social network theories | Networks: definition, metrics Social networks: Design, Technology, Features, and Impacts Social networks analysis: Why and How |
| 3 | 2024-09-11 | Theoretical foundations: Information Diffusion | Models of information diffusion Case study analysis |
| 4 | 2024-09-18 | Theoretical foundations: Social capital | Definitions and measures Role of social technologies on social capital |
| 5 | 2024-09-25 | Theoretical foundations: social behavior theories | Theories of personal behavior Theories of social behaviors Mass communication theories |
| 6 | 2024-10-02 | Project topic and team formation | Instructor will provide feedback for each team on the general idea, methods, and plan of their project Project ideas due |
| 7 | 2024-10-09 | Social software | What is social software? Connecting people through technology Open source software development Reading assignment 1: in-class presentation (Harris, C., Johnson, A. G., Palmer, S., Yang, D., & Bruckman, A. (2023). "Honestly, I Think TikTok has a Vendetta Against Black Creators": Understanding Black Content Creator Experiences on TikTok. Proceedings of the CSCW conference) |
| 8 | 2024-10-16 | Midterm exam | Topics: theoretical foundations |
| 9 | 2024-10-23 | Virtual Worlds | Designing virtual worlds MUD Metaverse Virtual identity |
| 10 | 2024-10-30 | Collaborative Technologies | Team communication Computer supported collaboration tools Content sharing Team communication in virutal worlds Reading assignment 2: in-class presentation (Weld, G., Zhang, A. X., & Althoff, T. (2024, May). Making online communities ‘better’: a taxonomy of community values on reddit. In Proceedings of the International AAAI Conference on Web and Social Media.) |
| 11 | 2024-11-06 | Social data analysis | Visualization and sense-making of social data Social and collaborative exploration of data Collecting social traces Social media APIs |
| 12 | 2024-11-13 | No lecture | Project work time |
| 13 | 2024-11-20 | Socially intelligent computing | Collective intelligence Content based recommender systems Collaborative filtering recommender systems Social data analysis assignment due |
| 14 | 2024-11-27 | No class | Thanksgiving break |
| 15 | 2024-12-04 | Social computing: ethics and societal impact | Impact on physical and psychological well-being Social computing for social good Ethics and privacy in social computing |
| 16 | 2024-12-11 | Final project | Final project presentations and report |
COURSE POLICIES
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.