Towards Characterization of Actor Evolution and Interactions in News Corpora

  • Rohan Choudhary
  • Sameep Mehta
  • Amitabha Bagchi
  • Rahul Balakrishnan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4956)

Abstract

The natural way to model a news corpus is as a directed graph where stories are linked to one another through a variety of relationships. We formalize this notion by viewing each news story as a set of actors, and by viewing links between stories as transformations these actors go through. We propose and model a simple and comprehensive set of transformations: create, merge, split, continue, and cease. These transformations capture evolution of a single actor and interactions among multiple actors. We present algorithms to rank each transformation and show how ranking helps us to infer important relationships between actors and stories in a corpus. We demonstrate the effectiveness of our notions by experimenting on large news corpora.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Rohan Choudhary
    • 1
  • Sameep Mehta
    • 2
  • Amitabha Bagchi
    • 1
  • Rahul Balakrishnan
    • 1
  1. 1.Indian Institute of TechnologyNew DelhiIndia
  2. 2.IBM India Research LabNew DelhiIndia

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