Ranking companies on the web using social network mining

Yingzi Jin, Yutaka Matsuo, Mitsuru Ishizuka

研究成果: Chapter

9 引用 (Scopus)

抜粋

Social networks have garnered much attention recently. Several studies have been undertaken to extract social networks among people, companies, and so on automatically from the web. For use in social sciences, social networks enable analyses of the performance and valuation of companies. This paper describes an attempt to learn ranking of companies from a social network that has been mined from the web. For example, if we seek to rank companies by market value, we can extract the social network of the company from the web and discern and subsequently learn a ranking model based on the social network. Consequently, we can predict the ranking of a new company by mining its relations to other companies. Using our approach, we first extract relational data of different kinds from the web. We then construct social networks using several relevance measures in addition to text analysis. Subsequently, the relations are integrated to maximize the ranking predictability. We also integrate several relations into a combined-relational network and use the latest ranking learning algorithm to obtain the ranking model. Additionally, we propose the use of centrality scores of companies on the network as features for ranking. We conducted an experiment using the social network among 312 Japanese companies related to the electrical products industry to learn and predict the ranking of companies according to their market capitalization. This study specifically examines a new approach to using web information for advanced analysis by integrating multiple relations among named entities.

元の言語English
ホスト出版物のタイトルStudies in Computational Intelligence
ページ137-151
ページ数15
172
DOI
出版物ステータスPublished - 2009
外部発表Yes

出版物シリーズ

名前Studies in Computational Intelligence
172
ISSN(印刷物)1860949X

ASJC Scopus subject areas

  • Artificial Intelligence

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  • これを引用

    Jin, Y., Matsuo, Y., & Ishizuka, M. (2009). Ranking companies on the web using social network mining. : Studies in Computational Intelligence (巻 172, pp. 137-151). (Studies in Computational Intelligence; 巻数 172). https://doi.org/10.1007/978-3-540-88081-3_8