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CatSent: a Catalan sentiment analysis website

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Abstract

In this paper we investigate, analyze and compare sentimental analysis methodologies in Catalan tweets. The main goal is to develop a high-performance Catalan classifier. There are three main steps: Catalan language preprocessing tool, classification model and corpus training. The preprocessing tool is used for cleaning and extracting features from a document (or tweet). This is a key step due to the great morphological complexity of the Catalan language. The tool will remove empty words from the text and find the roots of other words. The classification algorithm will divide the tweet into “positive” and “negative” classes. To choose the best algorithm, five models are compared: Naïve Bayes, Maximum Entropy, Support Vector Machine, Decision Tree and Neural Networks. Finally, the corpus will be used for training and testing these methods. There is no known public corpus in Catalan, so we created one using a lexicon-based approach. This work aims to enable the tools to carry out sentiment analysis studies in the Catalan language. The last step is to develop a public web service with the best classification model achieved where users will be able to check its effectiveness.

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Notes

  1. GitHup repository: https://github.com/pbalaguer19/catalan-sentiment-analysis

  2. API repository: https://github.com/pbalaguer19/catsent-api/

  3. NumPy: http://www.numpy.org

  4. Pandas: http://pandas.pydata.org

  5. TensorFlow: https://www.tensorflow.org

  6. Language detection service: https://detectlanguage.com

  7. Project on Github: https://github.com/pbalaguer19/catalan-sentiment-analysis

  8. Ranks NL: http://www.ranks.nl/stopwords/catalan

  9. LaTeL: http://latel.upf.edu/morgana/altres/pub/ca_stop.htm

  10. In geometry, a hyperplane is a division of a space into two parts

  11. http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow

  12. https://github.com/dennybritz/cnn-text-classification-tf

  13. https://github.com/dennybritz/cnn-text-classification-tf

  14. RESTful Web services are one way of providing interoperability between computer systems on the Internet.

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Acknowledgements

This work was supported by the Ministerio de Economía y Competitividad under contract TIN2017-84553-C2-2-R. IT, JV, JM, JR and FS are members of the research group 2017-SGR363, funded by the Generalitat de Catalunya. Besides, this research is partly supported by the European Union FEDER (CAPAP-H6 network TIN2016-81840-REDT). The research leading to these results has received funding from RecerCaixa.

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Authors and Affiliations

  1. Parc Científic i Tecnològic de Lleida, Building H3, ground floor, 25003, Lleida, Spain

    Pau Balaguer

  2. Department of Computer Science, University of Lleida, Jaume II 69, 25001, Lleida, Spain

    Ivan Teixidó, Jordi Vilaplana, Jordi Mateo & Francesc Solsona

  3. Department of AEGERN, University of Lleida, Jaume II 73, 25001, Lleida, Spain

    Josep Rius

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  1. Pau Balaguer
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  2. Ivan Teixidó
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  3. Jordi Vilaplana
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  4. Jordi Mateo
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  5. Josep Rius
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  6. Francesc Solsona
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Correspondence to Francesc Solsona.

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Balaguer, P., Teixidó, I., Vilaplana, J. et al. CatSent: a Catalan sentiment analysis website. Multimed Tools Appl 78, 28137–28155 (2019). https://doi.org/10.1007/s11042-019-07877-7

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