articleNeural Information Processing SystemsDec 3, 2012Closed access

Learning to Discover Social Circles in Ego Networks

Stanford University

Abstract

Our personal social networks are big and cluttered, and currently there is no good way to organize them. Social networking sites allow users to manually categorize their friends into social circles (e.g. 'circles' on Google+, and 'lists' on Facebook and Twitter), however they are laborious to construct and must be updated whenever a user's network grows. We define a novel machine learning task of identifying users' social circles. We pose the problem as a node clustering problem on a user's ego-network, a network of connections between her friends. We develop a model for detecting circles that combines network structure as well as user profile information. For each circle we learn its members and the…

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Authors

2

Topics & keywords

Keywords
  • Computer science
  • Similarity (geometry)
  • Construct (python library)
  • Cluster analysis
  • Set (abstract data type)
  • Categorization
  • Task (project management)
  • Node (physics)
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