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Semi-supervised Sentiment Annotation of Large Corpora

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Computational Processing of the Portuguese Language (PROPOR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11122))

Abstract

Huge annotated corpora are relevant for many Natural Language Processing tasks such as Sentiment Analysis. However, a manual and more precise annotation is always costly and becomes prohibitive when the corpus is too large. This paper presents a semi-supervised learning based framework for extending sentiment annotated corpora with unlabeled data, named CasSUL. The framework was used to extend in eight times TTsBR, a corpus of 15.000 tweets in Brazilian Portuguese manually annotated in three polarity classes. The extended annotated corpus was used to train several polarity classifiers and the results show that some combinations of classifier and features can preserve the annotation quality of the original corpus in the resulting corpus.

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Acknowledgement

We acknowledge financial support from CNPq and CAPES for the financial support during the experiment that originated this research paper.

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Authors and Affiliations

  1. Núcleo Interinstitucional de Linguística Computacional, Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Paulo, Brazil

    Henrico Bertini Brum & Maria das Graças Volpe Nunes

Authors
  1. Henrico Bertini Brum
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  2. Maria das Graças Volpe Nunes
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Corresponding author

Correspondence to Henrico Bertini Brum .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Aline Villavicencio

  2. Instituto de Informática - UFRGS, Porto Alegre, Brazil

    Viviane Moreira

  3. INESC-ID, Lisbon, Portugal

    Alberto Abad

  4. UFSCAR, Sao Carlos, Brazil

    Helena Caseli

  5. Centro Singular de Investigación en Tecnoloxías, Universidade de Santiago de Compostela, Santiago de Compostela, La Coruña, Spain

    Pablo Gamallo

  6. Université de Toulon, Parc Scientifique Technologique Luminy, Marseille, France

    Carlos Ramisch

  7. Centro de Informática e Sistemas, Universidade de Coimbra, Coimbra, Portugal

    Hugo Gonçalo Oliveira

  8. Federal University of Technology, Dois Vizinhos, Paraná, Brazil

    Gustavo Henrique Paetzold

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Brum, H.B., Nunes, M.d.G.V. (2018). Semi-supervised Sentiment Annotation of Large Corpora. In: Villavicencio, A., et al. Computational Processing of the Portuguese Language. PROPOR 2018. Lecture Notes in Computer Science(), vol 11122. Springer, Cham. https://doi.org/10.1007/978-3-319-99722-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-99722-3_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99721-6

  • Online ISBN: 978-3-319-99722-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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