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Automatic Sentiment Analysis in Polish Language

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Machine Intelligence and Big Data in Industry

Part of the book series: Studies in Big Data ((SBD,volume 19))

Abstract

We introduce fully automated process for sentiment analysis in short texts in Polish language. Process consists of (a) generation of emotion lexicon using Twitter annotated messages (b) building sentiment data set using annotated messages and the generated lexicon, (c) training NEAT genetic algorithm using previously prepared data set and (d) the final evaluation using 10 fold cross validation. We show that this method provides good results and can be used to simplify sentiment analysis processes for Polish language content.

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Author information

Authors and Affiliations

  1. Natural Language Processing Laboratory, National Information Processing Institute, Niepodleglosci 188 B Avenue, 00-608, Warsaw, Poland

    Antoni Sobkowicz

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  1. Antoni Sobkowicz
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Correspondence to Antoni Sobkowicz .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

    Dominik Ryżko

  2. Institute of Computer Science, Warsaw University of Technology, Abo, Poland

    Piotr Gawrysiak

  3. Institute of Computer Science, Warsaw University of Technology, Warszawa, Poland

    Marzena Kryszkiewicz

  4. Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

    Henryk Rybiński

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Sobkowicz, A. (2016). Automatic Sentiment Analysis in Polish Language. In: Ryżko, D., Gawrysiak, P., Kryszkiewicz, M., Rybiński, H. (eds) Machine Intelligence and Big Data in Industry. Studies in Big Data, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-30315-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-30315-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30314-7

  • Online ISBN: 978-3-319-30315-4

  • eBook Packages: EngineeringEngineering (R0)

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