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A Novel Web Metric for the Evaluation of Internet Trends

Authors: Radek Malinský, Ivan Jelínek


Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend.

Keywords: Blog, Sentiment Analysis, Web 2.0, Webometrics

Digital Object Identifier (DOI):

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[1] M. Thelwall, P. Wouters, and J. Fry, "Information-centered research for large-scale analyses of new information sources," Journal of the American Society for Information Science and Technology, vol. 59, pp. 1523-1527, July 2008.
[Online]. Available:
[2] Internet World Stats - Usage and Population Statistics, "Internet usage statistics."
[Online]. Available: htm
[3] S.-K. Han, D. Shin, J.-Y. Jung, and J. Park, "Exploring the relationship between keywords and feed elements in blog post search," World Wide Web, vol. 12, pp. 381-398, 2009, 10.1007/s11280-009-0067-3.
[Online]. Available:
[4] M. Thelwall, "Blog searching: The first general-purpose source of retrospective public opinion in the social sciences?" 289, vol. 31, pp. 277+, 2007.
[5] B. Pang and L. Lee, "Opinion mining and sentiment analysis," Foundations and Trends in Information Retrieval, vol. 2, no. 1-2, pp. 1- 135, Jan. 2008.
[6] R. MalinskÛ and I. Jelínek, "Improvements of webometrics by using sentiment analysis for better accessibility of the web," in Current Trends in Web Engineering, ser. Lecture Notes in Computer Science, F. Daniel and F. Facca, Eds. Springer Berlin / Heidelberg, vol. 6385, pp. 581-586.
[Online]. Available: 59
[7] I. Aguillo, J. Ortega, M. Fern'andez, and A. Utrilla, "Indicators for a webometric ranking of open access repositories," Scientometrics, vol. 82, pp. 477-486, 2010, 10.1007/s11192-010-0183-y.
[Online]. Available:
[8] M. Thelwall, "Introduction to webometrics: Quantitative web research for the social sciences." San Rafael, CA : Morgan & Claypool, 2009.
[9] M. Potthast and S. Becker, "Opinion summarization of web comments," in Advances in Information Retrieval, ser. Lecture Notes in Computer Science, C. Gurrin, Y. He, G. Kazai, U. Kruschwitz, S. Little, T. Roelleke, S. R├╝ger, and K. van Rijsbergen, Eds. Springer Berlin / Heidelberg, 2010, vol. 5993, pp. 668-669, 10.1007/978-3-642-12275-0 73.
[Online]. Available: 73
[10] R. Prabowo and M. Thelwall, "Sentiment analysis: A combined approach," Journal of Informetrics, vol. 3, no. 2, pp. 143-157, 2009.
[11] K. Toutanova, D. Klein, C. Manning, and Y. Singer, "Feature-rich partof- speech tagging with a cyclic dependency network," in HLT-NAACL, 2003, pp. 252-259.
[12] R. Agrawal, S. Gollapudi, K. Kenthapadi, N. Srivastava, and R. Velu, "Enriching textbooks through data mining," in Proceedings of the First ACM Symposium on Computing for Development, ser. ACM DEV -10. New York, NY, USA: ACM, 2010, pp. 19:1-19:9.
[Online]. Available:
[13] S. Baccianella, A. Esuli, and F. Sebastiani, "Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining," in Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC-10), N. Calzolari, K. Choukri, B. Maegaard, J. Mariani, J. Odijk, S. Piperidis, M. Rosner, and D. Tapias, Eds. Valletta, Malta: European Language Resources Association (ELRA), may 2010.
[14] A. Esuli and F. Sebastiani, "Sentiwordnet: A publicly available lexical resource for opinion mining," in In Proceedings of the 5th Conference on Language Resources and Evaluation (LREC-06), 2006, pp. 417-422.