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Spanish Corpus for Sentiment Analysis Towards Brands

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10458)

Abstract

Posts published in the social media are a good source of feedback to assess the impact of advertising campaigns. Whereas most of the published corpora of messages in the Sentiment Analysis domain tag posts with polarity labels, this paper presents a corpus in Spanish language where tagging has been made using 8 predefined emotions: love-hate, happiness-sadness, trust-fear, satisfaction-dissatisfaction. In every post, extracted from Twitter, sentiments have been annotated towards each specific brand under study. The corpus is published as a collection of RDF resources with links to external entities. Also a vocabulary describing this emotion classification along with other relevant aspects of customer’s opinion is provided.

Keywords

  • Corpus
  • Sentiment analysis
  • NLP
  • Opinion mining

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Fig. 1.
Fig. 2.

Notes

  1. 1.

    The SAB corpus is available online offering only the ID of the tweets.

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Acknowledgments

This work has been partially supported by LPS-BIGGER (IDI-20141259, Ministerio de Economía y Competitividad), a research assistant grant by the Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid partially founded by the European Social Fund (PEJ16/TIC/AI-1984) and a Juan de la Cierva contract.

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Correspondence to María Navas-Loro .

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Navas-Loro, M., Rodríguez-Doncel, V., Santana-Perez, I., Sánchez, A. (2017). Spanish Corpus for Sentiment Analysis Towards Brands. In: Karpov, A., Potapova, R., Mporas, I. (eds) Speech and Computer. SPECOM 2017. Lecture Notes in Computer Science(), vol 10458. Springer, Cham. https://doi.org/10.1007/978-3-319-66429-3_68

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