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Analysis of Social Information Networks
COMS 6998-2, Spring 2011, Columbia University
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Social information networks are the structures characterizing the connections between individuals (e.g., through friendship, influence, opportunity of contacts and information exchanges) and their attributes (e.g., their sociological profiles, communities of interests, and online behaviors such as viewing, purchasing, rating).
In the last decade, more and more information has been collected through web and social media applications about users behavior and interaction. Through them it is now possible to observe social dynamics at unprecedented scale, but also to understand social information networks from a computational point of view.
The objective of this course is for the students to acquire the theoretical skills allowing them to understand social information networks and design algo- rithms that take advantage of users’ behavior and interactions. If you wish to understand from first principle how information propagates over Facebook or Twitter, how to model and exploit influence between users, and how search en- gine and recommender systems find relevant information, this series of lectures will help you find these answers.
Organization of the course:
The first half of the course (8 lectures) is de- voted to understand the set of classical results that form the core of our current understanding of social information networks: properties of social networks and the small world phenomenon, power law and popularity dynamics, influence and epidemics, ranking, embedding, partitioning.
The second half of the course (6 lectures) takes a snapshot of the current online social applications and services used today (user generated content, blogs, online social networks) with a emphasis on recent measurements and areas of growing interests (i.e., mobile services and economic aspects of social networks).
Instructor: A. Chaintreau. TA: Z. Abbassi.
Grading scheme: mid-term exam (30%), class participation (scribe, paper presentation) (30%), final project (case study or topic review) (40%).
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