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, psychology, and sociology. 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.
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:
- Class participation [10 points]
- Social data analysis assignment [25 points]
- Wikipedia assignment [25 points]
- Final project [40 points]
OFFICE HOUR:
Thursday 1:00-2:00 pm, or by appointment, 709 Information Science Building (135 North Bellefield Avenue)
TOPICS TO BE COVERED:
- Social software
- Social computing technologies
- Social information processing
- Human computation and collective intelligence
- Social capital
- Online communities
- Socialization of newcomers
- Encouraging contribution
- Diversity, conflict and coordination
- Evaluation methodologies
- Visualization and sense making
- Research ethics
SYLLABUS:
# | Date | Topic | Details |
---|---|---|---|
1 | Jan 7, 2016 | Introduction and overview | introduction to course students' introduction |
2 | Jan 14, 2016 | Social Network Sites and Social Media | Blogging and microblogging: what are blogs? Who blogs? Social networks: Design, Technology, Features, and Impacts |
3 | Jan 21, 2016 | Distributed collaboration | Wikis and Wikipedia Computer supported collaboration tools Content sharing Wikipedia assignment step 1 posted |
4 | Jan 28, 2016 | Social information processing | Tagging Social navigation Social search Wikipedia assignment step 1 DUE Project ideas |
5 | Feb 4, 2016 | Recommender systems | content based collaborative filtering chalenges of social information processing |
6 | Feb 11, 2016 | Evaluation methodologies and research ethics | Data collection Data analysis Usability studies Conducting research on the Internet Privacy IRB Wikipedia assignment step 2 posted |
7 | Feb 18, 2016 | Social data analysis | Visualization Sense-making APIs Wikipedia Social data analysis assignment posted |
8 | Feb 25, 2016 | Midterm | Project Report |
9 | March 3, 2016 | No class | Work on projects |
10 | March 10, 2016 | No class | Spring Break |
11 | March 17, 2016 | Online communities - Socialization of newcomers | Membership lifecycles Dealing with newcomers Socialization Wikipedia assignment step 2 DUE |
12 | March 24, 2016 | Online communities - Encouraging contribution | under-contribution problem Encouraging contributions to online communities Strategies supported by social science theories Social data analysis assignment DUE Wikipedia assignment step 3 posted |
13 | March 31, 2016 | Social network analysis | Networks: definition, metrics Modeling and visualization Practical applications |
14 | April 7, 2016 | Social capital | Definitions and measures Social capital and social networks Role of online communities on social capital |
15 | April 14, 2016 | Human computation and collective intelligence | Crowdsourcing Mechanical turk Purposeful games Creative crowdsourcing Wikipedia assignment step 3 DUE |
16 | April 21, 2016 | Final project | Final project poster session |
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 class participation credit is engineered to encourage your attendance.
Late Submissions: Homework or projects submitted after due date will be accepted, but your objective grade will be scaled so that you lose 10% of the grade for every late working day. I.e., if you will submit your work one week late, you will lose 70% of the grade.
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.