| Social Circle Analysis |
Background and summary: Given social network data from Facebook, Twitter, and/or GooglePlus, can you identify
the social circles within the network by combining user data and network structure? This has useful applications in
international security when trying to identify terrorist connections and in marketing and advertising. Goal: Use the data to identify social circles of people, use these social circles to suggest where this information would be valuable. Input data: This dataset consists of 'circles' (or 'friends lists') from Facebook. Facebook data was collected from survey participants using this Facebook app. The dataset includes node features (profiles), circles, and ego networks. Facebook data has been anonymized by replacing the Facebook-internal ids for each user with a new value. Also, while feature vectors from this dataset have been provided, the interpretation of those features has been obscured. For instance, where the original dataset may have contained a feature "political=Democratic Party", the new data would simply contain "political=anonymized feature 1". Thus, using the anonymized data it is possible to determine whether two users have the same political affiliations, but not what their individual political affiliations represent. You have access to the following data: Social Circles Facebook Relevant papers: Learning to Discover Social Circles in Ego Networks Bi-directional Joint Inference for User Links and Attributes on Large Social Graphs MGAE: Marginalized Graph Autoencoder for Graph Clustering Discovering Social Circles in Ego Networks |