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IJML 2012 Vol.2(3): 327-332
doi: 10.7763/IJMLC.2012.V2.139

Trend Analysis of News Topics on Twitter

Rong Lu , Qing Yang

  • National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Abstract

This paper focus on trend analysis of news topics on Twitter, which include trend prediction and reasons analysis for the changes of trend. We first present a novel method to predict the trends of topics on Twitter based on MACD (Moving Average Convergence-Divergence) indicator. It is one of the simplest and most effective tendency indicators in technique analysis of stocks. We improve the original MACD indicator according to the characteristics of news topics on Twitter, define a new concept as trend momentum and use it to predict the trend of news topics. Then, we propose some reasons for the variation of trends. Experimental results show that the trend prediction is simple and effective. And, the reasons for variation of trends are also verified.

Keywords

  • Trend analysis
  • trend prediction
  • twitter
139-L0028

How to Cite

Copied

Rong Lu and Qing Yang, "Trend Analysis of News Topics on Twitter," International Journal of Machine Learning, vol. 2, no. 3, pp. 327-332, 2012. https://doi.org/10.7763/IJMLC.2012.V2.139

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD