Social Computing - CS60017

Fall Semester - 2015-16

Instructors

Pawan Goyal and Animesh Mukherjee

Adjunct Faculty

Dr. Monojit Choudhury, Microsoft Research

Course Timings

Lectures

Wednesday - 11:30 - 12:25 (CSE-107)

Thursday - 10:30 -11:25 (CSE-107)

Friday - 8:30 - 10:25 (CSE-107)

Teaching Assistants

Abhijnan Chakraborty, Sankarsan Mridha

Announcements

Project Final Evaluation will be on November 14th. Exact schedule will be announced later.

Project Mid-Term Evaluation will be on September 26, 27. Exact schedule will be announced later.

Next Set of Lectures by Dr. Monojit Choudhury will be on October 12-14, 5:30 - 7:00 PM. Venue will be as follows:

October 12-13th : V-1 (Vikramshila Complex)

October 14th: F-127 (Main Building)

Dr. Monojit Choudhury will be giving the first set of lectures on August 19th (Wed) and August 20th (Thu) from 5:30 - 7:30 PM. The venue will be F-127, just opposite to the central library.

Classes start from July 23rd (Thursday) in CSE - 107.

Lecture Slides

July 23, 2015 Introduction
July 24-30, 2015 Hashtags on Twitter
July 31, 2015 Information Diffusion on Twitter
July 31, 2015 Link Farming in Twitter
August 05-06, 2015 Social Network: Basic Structure and Measure
August 19, 2015 NLP for Social Media: What, Why and How?
August 19, 2015 NLP for Social Media: Text Normalization
August 20, 2015 NLP for Social Media: Normalization with the Noisy Channel
August 20, 2015 NLP for Social Media: Processing Indic Language Social Media Context
August 26 - September 04, 2015 Opinion Dynamics
September 9-10, 2015 Random Walks
September 11, 2015 Supervised Random Walks
September 23rd - October 1st, 2015 Sampling, Entity Resolution
October 8-9th, 2015 Topic Models
October 12th, 2015 NLP for Social Media: Direct Processing of Social Media Data
October 13th, 2015 NLP for Social Media: Processing Multilingual Content
October 14th, 2015 NLP for Social Media: Sociolinguistics and Language-usage based studies
October 29-30, 2015 Recommendation Systems
November 4-12, 2015 Locality Sensitive Hashing, Link PRediction, Causality/Correlation

Class Problems

August 19-20, 2015 NLP for Social Media: Problems Solutions

Last Year Exam Questions

Mid-Term, 2014 Problems
End-Term, 2014 Problems

Course Contents

The major components of the course include
  1. Online Social Networks (OSNs)
    1. Introduction - Types of social networks (e.g., Twitter, Facebook), Measurement and Collection of Social Network Data
    2. Techniques to study different aspects of OSNs -- Follower-followee dynamics, link farming, spam detection, hashtag popularity and prediction, linguistic styles of tweets
  2. Models of Opinion Formation
    1. Opinion Dynamics - Continuous and Discrete Models
    2. Cultural, Language Dynamics - Axelrod Model and its variant, The Naming game, The Category Game
    3. Crowd Behavior- Flocking, Pedestrian behavior, Applause Dynamics and Mexican Wave
    4. Formation of Hierarchies - The Bonabeau Model, The advancement-decline Model
    5. Social spreading Phenomena- rumor spreading, gossip spreading
  3. Working with the Social Media Data
    4. [To be covered by Dr. Monojit Choudhury]
    1. Language usage over social media: Basic challenges – 1 [spelling variation]
    2. Language usage over social media: Basic challenges – 2 [transliteration & spelling]
    3. Processing social media text: Entity Extraction
    4. Processing social media text: POS tagging and parsing
  4. Fundamentals of Social Data Analytics
    1. Topic Models
    2. Modeling social interactions on the Web
    3. Random Walks
    4. Variants of random walk
  5. Applied Social Data Analytics
    1. Recommendation Systems
    2. Language dynamics and influence in online communities
    3. Community identification, link prediction and topical search in social networks
  6. Opinion, Sentiments and User Behavior
    7. [To be covered by Dr. Monojit Choudhury]
    1. Opinion/Emotion/Sentiment detection in Social Media text - 1
    2. Opinion/Emotion/Sentiment detection in Social Media text – 2
    3. User behavior through NLP: detecting symptoms of disease, depression, addiction
    4. User behavior through NLP: detecting user demographics and relations
  7. Other Advanced Topics
    1. Online experiments for Computational Social Science
    2. Big Data Sampling
    3. Entity Resolution

Text and Reference Literature

  1. Matthew A. Russell. Mining the Social Web: Data Mining Facebook, Twitter, Linkedin, Google+, Github, and More, 2nd Edition, O'Reilly Media, 2013.
  2. Jennifer Golbeck, Analyzing the social web, Morgan Kaufmann, 2013.
  3. Charu Aggarwal (ed.), Social Network Data Analytics, Springer, 2011.