Sentiment Analysis: Popularity of Candidates for the President of the United States
This article deals with the popularity of candidates for the president of the United States of America. The popularity is assessed according to public comments on the Web 2.0. Social networking, blogging and online forums (collectively Web 2.0) are for common Internet users the easiest way to share their personal opinions, thoughts, and ideas with the entire world. However, the web content diversity, variety of technologies and website structure differences, all of these make the Web 2.0 a network of heterogeneous data, where things are difficult to find for common users. The introductory part of the article describes methodology for gathering and processing data from Web 2.0. The next part of the article is focused on the evaluation and content analysis of obtained information, which write about presidential candidates.
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[8] R. MalinskÛ and I. Jelínek, "A Novel Web Metric for the Evaluation of
Internet Trends", Proceedings of World Academy of Science,
Engineering and Technology. 2011, vol. 7, no. 81, p. 504-507. ISSN
2010-376X.
[9] 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:
http://dx.doi.org/10.1007/s11192-010-0183-y
[10] M. Thelwall, "Introduction to webometrics: Quantitative web research
for the social sciences." San Rafael, CA : Morgan & Claypool, 2009.
[11] 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.
[12] 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.
[13] 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:
http://doi.acm.org/10.1145/1926180.1926204
[14] 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.
[15] 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.
[1] Internet World Stats - Usage and Population Statistics, "Internet usage
statistics." (Online). Available:
http://www.internetworldstats.com/stats.htm
[2] T. Berners-Lee, J. Hendler, and O. Lassila, "The semantic web",
Scientific American, May 2001.
[3] Thelwall, M., "Bibliometrics to Webometrics", Journal of Information
Science, 34(4), 605, 2008.
[4] Langville, A.N., Meyer, C.D., "Google's PageRank and Beyond: The
Science of Search Engine Rankings", Princeton University Press, 2006,
ISBN 978-0691122021
[5] 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: http://dx.doi.org/10.1007/978-3-642-16985-4 59
[6] 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: http://dx.doi.org/10.1007/978-3-642-12275-0 73
[7] R. Prabowo and M. Thelwall, "Sentiment analysis: A combined
approach," Journal of Informetrics, vol. 3, no. 2, pp. 143-157, 2009.
[8] R. MalinskÛ and I. Jelínek, "A Novel Web Metric for the Evaluation of
Internet Trends", Proceedings of World Academy of Science,
Engineering and Technology. 2011, vol. 7, no. 81, p. 504-507. ISSN
2010-376X.
[9] 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:
http://dx.doi.org/10.1007/s11192-010-0183-y
[10] M. Thelwall, "Introduction to webometrics: Quantitative web research
for the social sciences." San Rafael, CA : Morgan & Claypool, 2009.
[11] 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.
[12] 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.
[13] 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:
http://doi.acm.org/10.1145/1926180.1926204
[14] 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.
[15] 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.
@article{"International Journal of Business, Human and Social Sciences:64219", author = "Radek Malinský and Ivan Jelínek", title = "Sentiment Analysis: Popularity of Candidates for the President of the United States", abstract = "This article deals with the popularity of candidates for the president of the United States of America. The popularity is assessed according to public comments on the Web 2.0. Social networking, blogging and online forums (collectively Web 2.0) are for common Internet users the easiest way to share their personal opinions, thoughts, and ideas with the entire world. However, the web content diversity, variety of technologies and website structure differences, all of these make the Web 2.0 a network of heterogeneous data, where things are difficult to find for common users. The introductory part of the article describes methodology for gathering and processing data from Web 2.0. The next part of the article is focused on the evaluation and content analysis of obtained information, which write about presidential candidates.
", keywords = "Sentiment Analysis, Web 2.0, Webometrics.", volume = "6", number = "12", pages = "3726-3", }
