use case 1: Predicting an individual's behavior based on behaviors of that individual's local community

This usecase is from Zhe Wu

Use case 1: Predicting an individual's behavior based on behaviors of the individual's local community

Overview:  In a society, an individual's behavior can be heavily influenced by that individual's close friends.
   Examples of such behaviors include but not limited to alcohol consumption, health related habits,
   like/dislike products, and adopting/rejecting services. Specifically in the telecommunication domain,
   service providers pay a lot of attention to spotting potential churners. To the service providers, keeping
   existing customers is as important as gaining new customers. One way to identify potential churners is to
   1) model the underlying social network and call network as a graph with attributes describing users and
   their interactions, 2) run graph analytics against the graph to identify communities,
   and 3) rank existing users based on the attrition rate of their close friends in a community, and
   possibly other signals.

Features: graph clustering, vertex ranking

References
[1] The Influence of Parents and Friends on Adolescent Substance Use: A Multidimensional Approach
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3132133/pdf/nihms294477.pdf

[2] Collective Churn Prediction in Social Network
http://www.mysmu.edu/faculty/fdzhu/paper/ASONAM%2712.pdf

[3] Local Graph Sparsification for Scalable Clustering
http://www.cse.ohio-state.edu/%7Esatuluri/satuluri_sigmod11.pd

[4] Statistical Properties of Community Structure in Large Social and Information Networks
http://cs.stanford.edu/people/jure/pubs/ncp-www08.pdf

[5] Detecting community structure in networks
http://www-personal.umich.edu/~mejn/papers/epjb.pdf
-- 
All the best, Ashok

Received on Tuesday, 12 November 2013 11:30:27 UTC