Network analysis of narrative content in large corpora. (January 2015)

• Record Type: Journal Article
• Authors: SUDHAHAR, SAATVIGA; DE FAZIO, GIANLUCA; FRANZOSI, ROBERTO; CRISTIANINI, NELLO
• Is Part Of: Natural language engineering. Volume 21:Part 1(2015)
• Page Start: 81
• Page End: 112
• Publication Date: 2015-01
• Subjects: Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324913000247
• Languages: English
• ISSNs: 1351-3249

Abstract

<abstract abstract-type="normal"> <title>Abstract</title> <p>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.</p> </abstract>