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Stance Detection in Tweets Using a Majority Vote Classifier

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The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) (AMLTA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 723))

Abstract

The task of stance detection is to determine whether someone is in favor or against a certain topic. A person may express the same stance towards a topic using positive or negative words. In this paper, several features and classifiers are explored to find out the combination that yields the best performance for stance detection. Due to the large number of features, ReliefF feature selection method was used to reduce the large dimensional feature space and improve the generalization capabilities. Experimental analyses were performed on five datasets, and the obtained results revealed that a majority vote classifier of the three classifiers: Random Forest, linear SVM and Gaussian Naïve Bayes classifiers can be adopted for stance detection task.

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Authors and Affiliations

  1. Engineering Mathematics Department, Faculty of Engineering, Cairo University, Giza, Egypt

    Sara S. Mourad, Doaa M. Shawky & Hatem A. Fayed

  2. Zewail City of Science and Technology, Giza, Egypt

    Doaa M. Shawky, Hatem A. Fayed & Ashraf H. Badawi

Authors
  1. Sara S. Mourad
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  2. Doaa M. Shawky
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  3. Hatem A. Fayed
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  4. Ashraf H. Badawi
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Corresponding author

Correspondence to Sara S. Mourad .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Computers and Information Sciences, Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Faculty of Computers and Information, Department of Computer Science and Engineering, Mansoura University, Dakahlia, Egypt

    Mohamed Elhoseny

  4. Arab Academy for Science, Technology and Maritime Transport (AASTMT), Dokki, Egypt

    Mohamed Mostafa

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Mourad, S.S., Shawky, D.M., Fayed, H.A., Badawi, A.H. (2018). Stance Detection in Tweets Using a Majority Vote Classifier. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_37

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  • DOI: https://doi.org/10.1007/978-3-319-74690-6_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74689-0

  • Online ISBN: 978-3-319-74690-6

  • eBook Packages: EngineeringEngineering (R0)

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