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Network analysis of narrative content in large corpora

Published online by Cambridge University Press:  11 September 2013

SAATVIGA SUDHAHAR ,
GIANLUCA DE FAZIO ,
ROBERTO FRANZOSI  and
NELLO CRISTIANINI
SAATVIGA SUDHAHAR
Affiliation:
Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1TH, UK e-mail: saatviga.sudhahar@bristol.ac.uk, nello.cristianini@bristol.ac.uk
GIANLUCA DE FAZIO
Affiliation:
Department of Sociology, Emory University, Atlanta, GA 30322, USA e-mail: rfranzo@emory.edu, gdefazi@emory.edu
ROBERTO FRANZOSI
Affiliation:
Department of Sociology, Emory University, Atlanta, GA 30322, USA e-mail: rfranzo@emory.edu, gdefazi@emory.edu
NELLO CRISTIANINI
Affiliation:
Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1TH, UK e-mail: saatviga.sudhahar@bristol.ac.uk, nello.cristianini@bristol.ac.uk
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Abstract

We present a methodology for the extraction of narrative information from a large corpus. The key idea is to transform the corpus into a network, formed by linking the key actors and objects of the narration, and then to analyse this network to extract information about their relations. By representing information into a single network it is possible to infer relations between these entities, including when they have never been mentioned together. We discuss various types of information that can be extracted by our method, various ways to validate the information extracted and two different application scenarios. Our methodology is very scalable, and addresses specific research needs in social sciences.

Type
Articles
Information
Natural Language Engineering , Volume 21 , Issue 1 , January 2015 , pp. 81 - 112
Copyright
Copyright © Cambridge University Press 2013 

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