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Topic Modeling over Text Streams from Social Media

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Text, Speech, and Dialogue (TSD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9924))

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Abstract

Topic modeling becomes a popular research area which shows us new way to search, browse and summarize large amount of texts. Methods of topic modeling try to uncover the hidden thematic structure in document collections. Topic modeling in connection with social networks, which are one of the strongest communication tool and produces large amount of opinions and attitudes on world events, can be useful for analysis in case of crisis situations, elections, launching a new product on the market etc. For that reason we pro-pose a tool for topic modeling over text streams from social networks in this paper. Description of proposed tool is extended with practical experiments. Realized experiments shown promising results when using our tool on real data in comparison to state-of-the-art methods.

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Acknowledgments

The work presented in this paper was supported by the Slovak VEGA grant 1/0493/16 and Slovak KEGA grant 025TUKE-4/2015.

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Authors and Affiliations

  1. Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 04200, Košice, Slovakia

    Miroslav Smatana, Ján Paralič & Peter Butka

Authors
  1. Miroslav Smatana
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  2. Ján Paralič
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  3. Peter Butka
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Corresponding author

Correspondence to Miroslav Smatana .

Editor information

Editors and Affiliations

  1. Masaryk University , Brno, Czech Republic

    Petr Sojka

  2. Masaryk University , Brno, Czech Republic

    Aleš Horák

  3. Masaryk University , Brno, Czech Republic

    Ivan Kopeček

  4. Masaryk University , Brno, Czech Republic

    Karel Pala

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Smatana, M., Paralič, J., Butka, P. (2016). Topic Modeling over Text Streams from Social Media. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2016. Lecture Notes in Computer Science(), vol 9924. Springer, Cham. https://doi.org/10.1007/978-3-319-45510-5_19

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  • DOI: https://doi.org/10.1007/978-3-319-45510-5_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45509-9

  • Online ISBN: 978-3-319-45510-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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