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Spanish sentiment analysis in Twitter at the TASS workshop

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Abstract

This paper describes a support vector machine-based approach to different tasks related to sentiment analysis in Twitter for Spanish. We focus on parameter optimization of the models and the combination of several models by means of voting techniques. We evaluate the proposed approach in all the tasks that were defined in the five editions of the TASS workshop, between 2012 and 2016. TASS has become a framework for sentiment analysis tasks that are focused on the Spanish language. We describe our participation in this competition and the results achieved, and then we provide an analysis of and comparison with the best approaches of the teams who participated in all the tasks defined in the TASS workshops. To our knowledge, our results exceed those published to date in the sentiment analysis tasks of the TASS workshops.

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Fig. 1
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Notes

  1. Web site with links to the five editions of TASS (Taller de Anàlisis de Sentimientos en la SEPLN) workshop: http://www.sepln.org/workshops/tass/2016/tass2016.php.

  2. Web sites of the SA tasks at SemEval (International Workshop on Semantic Evaluation):

    https://www.cs.york.ac.uk/semeval-2013

    http://alt.qcri.org/semeval2014

    http://alt.qcri.org/semeval2015

    http://alt.qcri.org/semeval2016.

  3. http://www.sepln.org/workshops/tass/2012/tass2012.php.

  4. http://www.sepln.org/workshops/tass/2013/tass2013.php.

  5. http://www.sepln.org/workshops/tass/2014/tass2014.php.

  6. http://www.sepln.org/workshops/tass/2015/tass2015.php.

  7. http://www.sepln.org/workshops/tass/2016/tass2016.php.

  8. http://www.csie.ntu.edu.tw/~cjlin/liblinear/.

  9. We have considered multiple combination strategies. In this work, we present the combination with the best results.

  10. For this task, Accuracy is equal to Precision, Recall, and \(F_{beta=1}\) measures.

  11. The confidence interval is estimated by using the formula \(A \pm 1.96\sqrt{\frac{A(1-A)}{N}}\), where A is the Accuracy and N is the number of samples in the test data set.

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Acknowledgements

This work has been partially funded by the Spanish MINECO and FEDER founds under project ASLP-MULAN: Audio, Speech and Language Processing for Multimedia Analytics, TIN2014-54288-C4-3-R.

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  1. Universitat Politècnica de València, Camí de Vera, s/n., 46022, València, Spain

    Ferran Pla & Lluís-F. Hurtado

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  1. Ferran Pla
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  2. Lluís-F. Hurtado
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Correspondence to Ferran Pla.

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Pla, F., Hurtado, LF. Spanish sentiment analysis in Twitter at the TASS workshop. Lang Resources & Evaluation 52, 645–672 (2018). https://doi.org/10.1007/s10579-017-9394-7

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