Abstract
Building on a previous study that succeeded in mapping business competition positions at an industry level using Web co-link analysis, the current study attempted to improve Web co-link analysis by adding Web page content to obtain the mapping at a particular market segment level. This method combines the ideas of Web content mining with Web structure mining. The method was tested in the WiMAX sector of the telecommunication industry. Specifically, the keyword WiMAX was incorporated into queries that searched for co-links to pairs of company Websites. Two sets of data were collected: one with the proposed method and one with co-link search alone. The resulting two data matrices were analyzed using multidimensional scaling (MDS) to generate maps of business competition. The comparison between the two maps shows that the proposed method produced a map focusing on the WiMAX sector. The study also proposed the measure of reduction of co-link count that can be used to gauge the effectiveness of focusing the analysis on a particular sector. The reduction of co-link count could also be an easy and pragmatic measure for an analysis of a company’s competitiveness in a particular market segment.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alvarion (2006), Corporate fact sheet. Retrieved Nov. 27, 2006 from http://www.alvarion.com/upload/images/mediakit/factsheet/Corporate_FS_revD_LR.pdf.
Björneborn, L., Ingwersen, P. (2004), Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14): 1216–1227.
Google (2006), Google SOAP Search API Reference. Retrieved Aug. 18, 2006 from http://www.google.com/apis/reference.html#2_2.
Liu, B., Ma, Y., Yu, P. S. (2001), Discovering unexpected information from your competitors’ web sites, In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 26–29, 2001, San Francisco, U.S.A.
Liu, B, Ma, Y., Yu, P. S. (2003), Discovering business intelligence information by comparing company Web sites. In: Zhong, N., Liu, J., Yao, Y. (Eds), Web Intelligence. Berlin: Springer, 105–127.
Lu, Z., Yao, Y., Zhong, N. (2003), Web Log Mining. In: Zhong, N., Liu, J., Yao, Y. (Eds), Web Intelligence. Berlin: Springer, 173–194.
Madnick, S., Siegel, M. (2002), Seizing the opportunity: exploiting web aggregation, MIS Quarterly Executive, 1(1): 35–46.
Madria, S., Bhowmick, S. S., Ng, W. K., Lim, E. P. (1999), Research issues in web data mining. In: Proceedings of Data Warehousing and Knowledge Discovery, First International Conference, Florence, Italy, Aug. 30–Sept. 1, 1999. Lecture Notes in Computer Science, Vol. 1676, 303–312.
Maravedis (2006), WiMAX and Broadband Wireless (Sub-11Ghz) Worldwide Market Analysis & Trends 2006–2012. Retrieved Nov. 16, 2006 from http://www.wimax-industry.com/mk/mrv/maravedis/mkmv1b.htm.
Mena, J. (2001), WebMining for Profit: E-Business Optimization. Boston: Digital press.
Meulman, J., Heiser, W. (2001), SPSS Categories® 11.0. Chicago, USA: SPSS Inc.
Reid, E. (2003), Using Web link analysis to detect and analyze hidden Web communities. In: D. Vriens, (Ed.), Information and Communications Technology for Competitive Intelligence (pp. 57–84), Hilliard, Ohio: Ideal Group Inc.
Ortega J. L, Aguillo, I., Cothey, V., Scharnhorst, A. (2006), Maps of the academic web in the European Higher Education Area — An exploration of visual web indicators. In: Book of Abstracts, 9th International Conference on Science & Technology Indicators, pp. 107–110, Leuven, Belgium, Sept. 7–9, 2006.
Small, H. (1973), Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, July–August, 1973, 265–269.
Thelwall, M. (2004), Link analysis: An information science approach. San Diego: Academic Press.
Thelwall, M., Price, E. (2006), Language evolution and the spread of ideas: A procedure for identifying emergent hybrid word family members. Journal of the American Society for Information Science and Technology, 57(10): 1326–1337.
Thuraisingham, B. (2003), Web Data Mining and Applications in Business Intelligence and Counter-Terrorism. Boca Raton, Florida: CRC Press.
Vaughan, L., You, J. (2005), Mapping business competitive positions using Web co-link analysis. In: P. Ingwersen, B. Larsen (Eds), Proceedings of ISSI 2005 — the 10th International Conference of the International Society for Scientometrics and Informetrics, pp. 534–543, Stockholm, Sweden, July 24–28, 2005.
Vaughan, L., You, J. (2006), Keyword enhanced Web structure mining for business intelligence. In: Proceedings of the 2006 IEEE/ACM International Conference on Signal-Image Technology and Internet-Based Systems, Hammamet, Tunisia, Dec. 17–21, 2006.
Vaughan, L., Kipp, M.E.I., Gao, Y. (2007), Are co-linked business Websites really related? A link classification study. Online Information Review, 31(4): 440–450.
Wikipedia (2006), WiMAX. retrieved Nov. 16, 2006 from http://en.wikipedia.org/wiki/WiMAX
Wormell, I. (2001), Informetrics and Webometrics for measuring impact, visibility, and connectivity in science, politics, and business. Competitive Intelligence Review, 12(1): 12–23.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Vaughan, L., You, J. Content assisted web co-link analysis for competitive intelligence. Scientometrics 77, 433–444 (2008). https://doi.org/10.1007/s11192-007-1999-y
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-007-1999-y