Social Computing CS60017
AUTUMN SEMESTER 2023-24
AUTUMN SEMESTER 2023-24
ANNOUNCEMENTS
1. First class on Thursday, August 3
2. This is a research-oriented course that would require students to understand several CS research papers. There will be a term project / assignments that will involve substantial programming in Python. It is advisable to take this course only if you have the necessary background (see below).
3. Plagiarism in any form in the assignments / term-projects -- copying from other students or from online resources -- will be severely penalized.
4. Register for the Social Computing (CS60017) course using the following password key: SCSPGA23STU at https://moodlecse.iitkgp.ac.in/moodle/login/index.php.
5. Assignment 1 is up on CSE Moodle, Deadline: 15th September EOD.
6. Mid-semester exam on 25-09-2023 during 2 - 4 PM. Venue: CSE-107 (CSE department main building, ground floor).
7. Guest lecture by Dr. Koustuv Saha (https://koustuv.com/), Assistant Professor of Computer Science at the University of Illinois at Urbana-Champaign, on September 28. Talk title: "Measuring Wellbeing in Situated Contexts with Social Media and Multimodal Sensing: Promises and Perils".
Instructor
Saptarshi Ghosh (saptarshi@cse.iitkgp.ac.in)
Teaching Assistants
Soham Poddar (sohampoddar@kgpian.iitkgp.ac.in)
Sourjyadip Ray (sourjyadipray@gmail.com)
Class Timings and Venue
Wednesday 10:00 - 10:55
Thursday 09:00 - 09:55
Friday 11:00 - 11:55
Classroom: CSE 119 (CSE department, ground floor)
Pre-requisites for the course
Data structures and algorithms
Probability and Statistics
Basics of Machine Learning
Basics of Natural Language Processing
Basics of Graph algorithms
Programming in Python (there will be a programming-based term project)
Course evaluation
Mid-semester exam: 30%
End-semester exam: 40%
Assignments: 20%
Attendance: 10%
Text and Reference Literature
Social Network Data Analytics - Charu Aggarwal (ed.) - Springer, 2011
Mining of Massive Datasets - Jure Leskovec, Anand Rajaraman, Jeff Ullman
Research papers to be pointed out in class
Broad topics
Social network analysis -- structural properties, applications and challenges
Network centrality
Community structure in social networks
Useful users/content on social media -- topical experts, use of social media for real-time news, social search and recommendation
Harmful users/content on social media -- hate speech, fake news, spammers in social networks, etc.
Different types of social platforms -- E-commerce sites, Medical / health-related platforms
Bias and fairness in social computing systems