Word co-occurrences on Webpages as a measure of the relatedness of organizations: A new Webometrics concept

Liwen Vaughan and Justin You

Journal of Informetrics, 2010, vol. 4, issue 4, 483-491

Abstract: Web hyperlink analysis has been a key topic of Webometric research. However, inlink data collection from commercial search engines has been limited to only one source in recent years, which is not a promising prospect for the future development of the field. We need to tap into other Web data sources and to develop new methods. Toward this end, we propose a new Webometrics concept that is based on words rather than inlinks on Webpages. We propose that word co-occurrences on Webpages can be a measure of the relatedness of organizations. Word co-occurrence data can be collected from both general search engines and blog search engines, which expands data sources greatly. The proposed concept is tested in a group of companies in the LTE and WiMax sectors of the telecommunications industry. Data on the co-occurrences of company names on Webpages were collected from Google and Google Blog. The co-occurrence matrices were analyzed using MDS. The resulting MDS maps were compared with industry reality and with the MDS maps from co-link analysis. Results show that Web co-word analysis could potentially be as useful as Web co-link analysis. Google Blog seems to be a better source than Google for co-word data collection.

Keywords: Web co-link analysis; Web co-word analysis; Webometrics; Competitive intelligence (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:4:y:2010:i:4:p:483-491

DOI: 10.1016/j.joi.2010.04.005

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