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Extracting inter‐firm networks from the World Wide Web using a general‐purpose search engine

Extracting inter‐firm networks from the World Wide Web using a general‐purpose search engine Purpose – Social relations play an important role in a real community. Interaction patterns reveal relations among actors (such as persons, groups, firms), which can be merged to produce valuable information such as a network structure. This paper aims to present a new approach to extract inter‐firm networks from the web for further analysis. Design/methodology/approach – In this study extraction of relations between a pair of firms is obtained by using a search engine and text processing. Because names of firms co‐appear coincidentally on the web, an advanced algorithm is proposed, which is characterised by the addition of keywords (“relation keywords”) to a query. The relation keywords are obtained from the web using a Jaccard coefficient. Findings – As an application, a network of 60 firms in Japan is extracted including IT, communication, broadcasting, and electronics firms from the web and comprehensive evaluations of this approach are shown. The alliance and lawsuit relations are easily obtainable from the web using the algorithm. By adding relation keywords to named pairs of firms as a query, It is possible to collect target pages from the top of web pages more precisely than by only using the named pairs as a query. Practical implications – This study proposes a new approach for extracting inter‐firm networks from the web. The obtained network is useful in several ways. It is possible to find a cluster of firms and characterise a firm by its cluster. Business experts often make such inferences based on firm relations and firm groups. For that reason the firm network might enhance inferential abilities on the business domain. Also we might use obtained networks to recommend business partners based on structural advantages. The authors' intuition is that extracting a social network might provide information that is only recognisable from the network point of view. For example, the centrality of each firm is identified only after generating a social network. Originality/value – This study is a first attempt to extract inter‐firm networks from the web using a search engine. The approach is also applicable to other actors, such as famous persons, organisations or other multiple relational entities. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Online Information Review Emerald Publishing

Extracting inter‐firm networks from the World Wide Web using a general‐purpose search engine

Online Information Review , Volume 32 (2): 15 – Apr 11, 2008

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References (26)

Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
1468-4527
DOI
10.1108/14684520810879827
Publisher site
See Article on Publisher Site

Abstract

Purpose – Social relations play an important role in a real community. Interaction patterns reveal relations among actors (such as persons, groups, firms), which can be merged to produce valuable information such as a network structure. This paper aims to present a new approach to extract inter‐firm networks from the web for further analysis. Design/methodology/approach – In this study extraction of relations between a pair of firms is obtained by using a search engine and text processing. Because names of firms co‐appear coincidentally on the web, an advanced algorithm is proposed, which is characterised by the addition of keywords (“relation keywords”) to a query. The relation keywords are obtained from the web using a Jaccard coefficient. Findings – As an application, a network of 60 firms in Japan is extracted including IT, communication, broadcasting, and electronics firms from the web and comprehensive evaluations of this approach are shown. The alliance and lawsuit relations are easily obtainable from the web using the algorithm. By adding relation keywords to named pairs of firms as a query, It is possible to collect target pages from the top of web pages more precisely than by only using the named pairs as a query. Practical implications – This study proposes a new approach for extracting inter‐firm networks from the web. The obtained network is useful in several ways. It is possible to find a cluster of firms and characterise a firm by its cluster. Business experts often make such inferences based on firm relations and firm groups. For that reason the firm network might enhance inferential abilities on the business domain. Also we might use obtained networks to recommend business partners based on structural advantages. The authors' intuition is that extracting a social network might provide information that is only recognisable from the network point of view. For example, the centrality of each firm is identified only after generating a social network. Originality/value – This study is a first attempt to extract inter‐firm networks from the web using a search engine. The approach is also applicable to other actors, such as famous persons, organisations or other multiple relational entities.

Journal

Online Information ReviewEmerald Publishing

Published: Apr 11, 2008

Keywords: Worldwide web; Social networks; Information retrieval

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