DESCRIPTION:

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. The course is interdisciplinary, drawing from the fields of computer science, information science, and social psychology. 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.

COURSE FORMAT:

To address the pandemic circumstance, this course is designed following the flipped classroom model; i.e. lectures are going to be recorded and available online for you to watch. Every week we will meet for about one hour during the class time for discussion of concepts in the lectures and interaction around activities, assignments, and the project. The recorded lectures will be broken down into smaller topics to reduce the size of the recording to about 15 minutes. You can attend the synchronous component of the class online but there is also a physical room dedicated to this class for those who would like to attend in-person. As the instructor, I will be joining the class online through zoom. Lecture recordings will include activities that we will discuss during the class time.

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:

OFFICE HOUR:

Email or online meetings by appointment:

TOPICS TO BE COVERED:

SYLLABUS:

#DateTopicDetailsActivities
12021-01-20Introduction and overviewCourse logistics and requirements
Overview of what social computing is about and what you will learn in this course
Introduction
What is Social Computing?
Collective Wisdon
22021-01-27Connecting people through technology: social softwareWhat is social software?
What are examples of social software?
What should we know about social software
Carousel problem
Designing a blog software
We Feel Fine
Why does Twitter work as it works?
32021-02-03Distributed collaborationComputer supported collaboration tools
Content sharing
Open source software development
Project ideas due
42021-02-10Project topic and team formation Instructor and TA will provide feedback for each team on the general idea, methods, and plan of their project
In-class break out room discussions of project ideas
52021-02-17Social Networks and Social Network AnalysisNetworks: definition, metrics
Social networks: Design, Technology, Features, and Impacts
Social networks: Why and How
Submitting list of papers for literature review
62021-02-24Designing online communities: challenges and solutionsunder-contribution problem
Encouraging contributions to online communities
Quiz 1: Distributed collaboration and Social network analysis
72021-03-03Social computing research methods and research ethicsData collection
Data analysis
Usability studies
Conducting research on the Internet
Privacy
IRB
Literature review due
82021-03-10Social data analysisVisualization
Sense-making
92021-03-17Project progress reportIn-class presentation of developed project idea, progress report, and feedback on your projects
102021-03-24No classStudent self-care day
112021-03-31Analysis of social dataCollecting social traces: How and Why
Wikipedia
APIs
122021-04-07Social capitalDefinitions and measures
Social capital and social networks
Role of online communities on social capital

132021-04-14Socially intelligent computingCollective intelligence
Content based recommender systems
Collaborative filtering recommender systems
Social data analysis assignment due
142021-04-21Social information processingTagging
Social navigation
Social search
Social bots
Quiz 2: Social capital, Collective intelligence, and Recommender systems
152021-04-28Final projectFinal project presentations and report

COURSE POLICIES

Health and Safety Statement: In the midst of this pandemic, it is extremely important that you abide by public health regulations and University of Pittsburgh health standards and guidelines. While in class, at a minimum this means that you must wear a face covering and comply with physical distancing requirements; other requirements may be added by the University during the semester. These rules have been developed to protect the health and safety of all community members. Failure to comply with these requirements will result in you not being permitted to attend class in person and could result in a Student Conduct violation. For the most up-to-date information and guidance, please visit coronavirus.pitt.edu and check your Pitt email for updates before each class.

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 class participation credit is 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. There are 2 extra points for those who do not submit anything late.

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.