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Improving the Sentiment Analysis Process of Spanish Tweets with BM25

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Natural Language Processing and Information Systems (NLDB 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9612))

Abstract

The enormous growth of user-generated information of social networks has caused the need for new algorithms and methods for their classification. The Sentiment Analysis (SA) methods attempt to identify the polarity of a text, using among other resources, the ranking algorithms. One of the most popular ranking algorithms is the Okapi BM25 ranking, designed to rank documents according to their relevance on a topic. In this paper, we present an approach of sentiment analysis for Spanish Tweets based combining the BM25 ranking function with a Linear Support Vector supervised model. We describe the implemented procedure to adapt BM25 to the peculiarities of SA in Twitter. The results confirm the potential of the BM25 algorithm to improve the sentiment analysis tasks.

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Notes

  1. 1.

    Workshop on Sentiment Analysis at SEPLN Conference.

  2. 2.

    http://www.sepln.org/.

  3. 3.

    http://scikit-learn.org/.

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Authors and Affiliations

  1. DeustoTech-Deusto Institute of Technology, Universidad de Deusto, Avenida de las Universidades 24, 48007, Bilbao, Spain

    Juan Sixto, Aitor Almeida & Diego López-de-Ipiña

Authors
  1. Juan Sixto
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  2. Aitor Almeida
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  3. Diego López-de-Ipiña
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Corresponding author

Correspondence to Juan Sixto .

Editor information

Editors and Affiliations

  1. ConservatoireNational desArts et Métiers, Paris, France

    Elisabeth Métais

  2. University of Salford, Salford, United Kingdom

    Farid Meziane

  3. University of Salford, Salford, United Kingdom

    Mohamad Saraee

  4. Oakland University, Rochester, Michigan, USA

    Vijayan Sugumaran

  5. University of Salford, Salford, United Kingdom

    Sunil Vadera

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© 2016 Springer International Publishing Switzerland

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Sixto, J., Almeida, A., López-de-Ipiña, D. (2016). Improving the Sentiment Analysis Process of Spanish Tweets with BM25. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_26

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  • DOI: https://doi.org/10.1007/978-3-319-41754-7_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41753-0

  • Online ISBN: 978-3-319-41754-7

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