Word co-occurrences on Webpages as a measure of the relatedness of organizations: A new Webometrics concept |
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| Authors: | Liwen Vaughan Justin You |
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| Institution: | 1. Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431-0991, USA;2. Faculty of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Technion City, Haifa 32000, Israel;3. Ecole Centrale Paris,, 92290 Châtenay-Malabry, France |
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| 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. |
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