Scientometrics

, Volume 93, Issue 1, pp 217–232

Exploring Web keyword analysis as an alternative to link analysis: a multi-industry case

Article

DOI: 10.1007/s11192-012-0640-x

Cite this article as:
Vaughan, L. & Romero-Frías, E. Scientometrics (2012) 93: 217. doi:10.1007/s11192-012-0640-x

Abstract

The study explored the feasibility of using Web keyword analysis as an alternative to link analysis and tested the feasibility in a multi-industry environment. The keyword is the organization’s name, in this case the company name. American companies from five industries were included in the study. The study found that the Web visibility of a company as measured by the number of Webpages on which the company name appears correlates with the company’s business measures (revenue, profits, and assets). The correlation coefficients are similar to that between the inlink counts and the business measures. This suggests that the keyword count (searched by the company name) could replace inlink count as an alternative indicator of some commonly used business measures. The co-word (the co-occurrence of the names of two companies on Webpages) count was used as a measure of the relatedness of the two companies. Multidimensional scaling (MDS) analysis was applied to the co-word matrices and generated MDS maps that showed relationships among companies in a multi-industry context. Keyword data were collected from three different types of Websites (general Websites, blog sites, and Web news sites) and results were compared. The study found blog sites to be the better source to collect data for this type of study. The comparison of MDS maps generated from co-link data and the blog co-word data showed that the co-word analysis is as effective as co-link analysis in mapping business relationships. The value of the study is not limited to the business sector as the co-word method could be applied to analysing relationships among other types of organizations.

Keywords

Web keyword analysis Web visibility Business performance Business relationships Webometrics 

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2012

Authors and Affiliations

  1. 1.Faculty of Information and Media StudiesUniversity of Western OntarioLondonCanada
  2. 2.Department of Accounting and FinanceUniversity of GranadaGranadaSpain

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