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International Conference on Flexible Query Answering Systems

FQAS 2019: Flexible Query Answering Systems pp 166–175Cite as

Generalized Association Rules for Sentiment Analysis in Twitter

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11529)

Abstract

Association rules have been widely applied in a variety of fields over the last few years, given their potential for descriptive problems. One of the areas where the association rules have been most prominent in recent years is social media mining. In this paper, we propose the use of association rules and a novel generalization of these based on emotions to analyze data from the social network Twitter. With this, it is possible to summarize a great set of tweets in rules based on 8 basic emotions. These rules can be used to categorize the feelings of the social network according to, for example, a specific character.

Keywords

  • Association rules
  • Sentiment analysis
  • Social media mining
  • Generalized association rules

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Acknowledgment

This research paper is part of the COPKIT project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 786687.

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Authors and Affiliations

  1. Department of Computer Science and A.I., University of Granada, Daniel Saucedo Aranda, s/n, 18014, Granada, Spain

    J. Angel Diaz-Garcia, M. Dolores Ruiz & Maria J. Martin-Bautista

Authors
  1. J. Angel Diaz-Garcia
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  2. M. Dolores Ruiz
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  3. Maria J. Martin-Bautista
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Corresponding author

Correspondence to J. Angel Diaz-Garcia .

Editor information

Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Alfredo Cuzzocrea

  2. University of Calabria, Rende, Italy

    Prof. Sergio Greco

  3. Legind Technologies , Esbjerg , Denmark

    Prof. Dr. Henrik Legind Larsen

  4. University of Calabria, Rende, Italy

    Prof. Domenico Saccà

  5. Roskilde University, Roskilde, Denmark

    Prof. Troels Andreasen

  6. Roskilde University, Roskilde, Denmark

    Prof. Henning Christiansen

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Diaz-Garcia, J.A., Ruiz, M.D., Martin-Bautista, M.J. (2019). Generalized Association Rules for Sentiment Analysis in Twitter. In: Cuzzocrea, A., Greco, S., Larsen, H., Saccà, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2019. Lecture Notes in Computer Science(), vol 11529. Springer, Cham. https://doi.org/10.1007/978-3-030-27629-4_17

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  • DOI: https://doi.org/10.1007/978-3-030-27629-4_17

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