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Tracking Researcher Mobility on the Web Using Snippet Semantic Analysis

  • Jorge J. García Flores
  • Pierre Zweigenbaum
  • Zhao Yue
  • William Turner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7614)

Abstract

This paper presents the Unoporuno system: an application of natural language processing methods to the sociology of migration. Our approach extracts names of people from a scientific publications database, refines Web search queries using bibliographical data and decides of the international mobility category of a person according to the location analysis of those snippets classified as mobility traces. In order to identify mobility traces, snippets are filtered with a name validation grammar, analyzed with mobility related semantic features and classified with a support vector machine. This classification method is completed by a semi-automatic one, where Unoporuno selects 5 snippets to help a sociologist decide upon the mobility status of authors. Empirical evidence for the automatic person classification task suggest that Unoporuno classified 78% of the mobile persons in the right mobility category, with F=0.71. We also present empirical evidence for the semi-automatic task: in 80% of the cases sociologist are able to choose the right category with a moderate level of inter-rater agreement (0.60) based on the 5 snippet selection.

Keywords

Mobility Status Noun Phrase Regular Expression Semantic Feature Computational Linguistics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jorge J. García Flores
    • 1
  • Pierre Zweigenbaum
    • 1
  • Zhao Yue
    • 2
  • William Turner
    • 1
  1. 1.LIMSI - CNRSOrsay CedexFrance
  2. 2.Université Paul ValéryMontpellierFrance

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