What drives social sentiment? An entropic measure-based clustering approach towards identifying factors that influence social sentiment polarity

Dionisios N. Sotiropoulos, Chris D. Kounavis, Panos Kourouthanassis, George M. Giaglis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Analyzing the public sentiment over social media streams constitutes an extremely demanding task mainly due to the difficulties that are imposed by the wide spectrum of discussion topics that underlie a given collection of posts. This paper addresses the problem of determining the underlying semantic factors that influence the social sentiment polarity in a given corpus of posts through the utilization of an entropic measure-based clustering approach. Extant studies examine the semantic structure of social network data primarily through topic modeling or sentiment analysis methods. The novelty of our approach lies upon the utilization of a semantically-aware clustering procedure that effectively combines topic modeling and sentiment analysis algorithms. Our approach extends the fundamental assumption behind traditional sentiment analysis methods, according to which sentiment can be associated with low level document features such as words, phrases or sentences. We argue that sentiment can be associated with higher level entities such as the semantic axes that span a given volume of posts, thus performing sentiment analysis at the topic level. Our experimentation provides strong evidence that combining topic modeling and sentiment analysis results by a semantically-aware clustering procedure can reveal the distribution of the overall public sentiment on the underlying semantic axes.

Original languageEnglish
Title of host publicationIISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications
PublisherIEEE Computer Society
Pages361-373
Number of pages13
ISBN (Print)9781479961719
DOIs
Publication statusPublished - 2014
Event5th International Conference on Information, Intelligence, Systems and Applications, IISA 2014 - Chania, Crete, Greece
Duration: 7 Jul 20149 Jul 2014

Other

Other5th International Conference on Information, Intelligence, Systems and Applications, IISA 2014
CountryGreece
CityChania, Crete
Period7/07/149/07/14

Keywords

  • Entropic Measure-based Clustering
  • Sentiment Analysis
  • Support Vector Machines
  • Topic Modelling

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  • Cite this

    Sotiropoulos, D. N., Kounavis, C. D., Kourouthanassis, P., & Giaglis, G. M. (2014). What drives social sentiment? An entropic measure-based clustering approach towards identifying factors that influence social sentiment polarity. In IISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications (pp. 361-373). [6878830] IEEE Computer Society. https://doi.org/10.1109/IISA.2014.6878830