Comparing Methods of Trend Assessment

  • Radek Malinský
  • Ivan Jelínek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8541)

Abstract

This paper deals with a comparison of selected webometric methods for the evaluation of Internet trends. Each of the selected methods uses a different methodology to the trend assessment: frequency, polarity, source quality. It can be assumed that a combination of individual methods can provide much more accurate results with respect to the desired area of interest. This will lead to improve the quality of search engines on the principle of webometrics and thereby the reduction of irrelevant web search results. The introductory part of the paper explains a concept and basic functional background for all selected webometric methods.

Keywords

Webometrics Web Mention Analysis Sentiment Analysis Social Network Analysis Trend Assessment 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Gehanno, J.F., Rollin, L., Darmoni, S.: Is the coverage of Google Scholar enough to be used alone for systematic reviews. BMC Medical Informatics and Decision Making 13(1) (2013)Google Scholar
  2. 2.
    Han, S.K., Shin, D., Jung, J.Y., Park, J.: Exploring the relationship between keywords and feed elements in blog post search. World Wide Web 12, 381–398 (2009)CrossRefGoogle Scholar
  3. 3.
    Jagtap, V.S., Pawar, K.: Analysis of different approaches to Sentence-Level Sentiment Classification. International Journal of Scientific Engineering and Technology 2(3), 164–170 (2013)Google Scholar
  4. 4.
    Liu, B.: Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies 5(1), 1–167 (2012)CrossRefGoogle Scholar
  5. 5.
    Montejo-Ráez, A., Martínez-Cámara, E., Martín-Valdivia, M.T., Urena-López, L.A.: Ranked WordNet Graph for Sentiment Polarity Classification in Twitter. Computer Speech & Language 41(11), 373–381 (2013)Google Scholar
  6. 6.
    Pak, A., Paroubek, P.: Twitter as a corpus for sentiment analysis and opinion mining. In: Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC 2010), Valletta, Malta (2010)Google Scholar
  7. 7.
    Thelwall, M.: Introduction to webometrics: Quantitative web research for the social sciences. Morgan & Claypool, San Rafael (2009)Google Scholar
  8. 8.
    Thelwall, M., Buckley, K., Paltoglou, G.: Sentiment in twitter events. Journal of the American Society for Information Science and Technology 62, 406–418 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Radek Malinský
    • 1
  • Ivan Jelínek
    • 1
  1. 1.Department of Computer Science and Engineering, Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech republic

Personalised recommendations