Examining the robustness of web co-link analysis

Purpose – The purpose of this paper is to examine the robustness of web co‐link analysis for business intelligence.Design/methodology/approach – The method is tested in two different Chinese industries, the electronics/IT industry and the chemical industry. Web co‐link data are collected in two different time periods from a different search engine in each period. Multidimensional scaling (MDS) is used to map the co‐link data into business competition positions.Findings – Web co‐link analysis is fairly robust in that the mapping results reflect fairly well the business competition landscape for both industries and in both time periods. The mapping results are better when the data collection is restricted to Chinese language webpages only. The study also finds that the Chinese webpages are very consumer‐oriented, a phenomenon that is not seen in previous studies of international companies.Originality/value – This paper contributes to the understanding of the robustness and applicability of the co‐link analy...

[1]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[2]  Liwen Vaughan,et al.  Are co-linked business web sites really related? A link classification study , 2007, Online Inf. Rev..

[3]  Liwen Vaughan,et al.  Links to commercial websites as a source of business information , 2004, Scientometrics.

[4]  Liwen Vaughan,et al.  Web hyperlink patterns and the financial variables of the global banking industry , 2010, J. Inf. Sci..

[5]  Liwen Vaughan,et al.  Why are hyperlinks to business Websites created? A content analysis , 2006, Scientometrics.

[6]  Philipp Mayr,et al.  Google Web APIs - an Instrument for Webometric Analyses? , 2006, ArXiv.

[7]  Liwen Vaughan,et al.  Patterns of web linking to heterogeneous groups of companies: The case of stock exchange indexes , 2010, Aslib Proc..

[8]  Judit Bar-Ban,et al.  Search Engine Ability to Cope With the Changing Web , 2004 .

[9]  Mike Thelwall Scientific Web Intelligence , 2009, Encyclopedia of Data Warehousing and Mining.

[10]  Liwen Vaughan,et al.  Mining web hyperlink data for business information: The case of telecommunications equipment companies , 2005 .

[11]  C. Lee Giles,et al.  Self-Organization and Identification of Web Communities , 2002, Computer.

[12]  José Luis Ortega,et al.  Maps of the academic web in the European Higher Education Area — an exploration of visual web indicators , 2007, Scientometrics.

[13]  Mike Thelwall,et al.  Extracting accurate and complete results from search engines: Case study windows live , 2008, J. Assoc. Inf. Sci. Technol..

[14]  Bhavani M. Thuraisingham,et al.  Web Data Mining and Applications in Business Intelligence and Counter-Terrorism , 2003 .

[15]  Mike Thelwall Scientific web intelligence: finding relationships in university webs , 2005, CACM.

[16]  L. Vaughan,et al.  Mapping business competitive positions using web co-link analysis , 2005 .

[17]  Raymond J. Mooney,et al.  Relational Data Mining with Inductive Logic Programming for Link Discovery , 2002 .

[18]  Edna O. F. Reid Using Web Link Analysis to Detect and Analyze Hidden Web Communities , 2004 .

[19]  Yanjun Zhang,et al.  Equal Representation by Search Engines? A Comparison of Websites across Countries and Domains , 2007, J. Comput. Mediat. Commun..