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International Conference on Applied Human Factors and Ergonomics

AHFE 2021: Advances in the Human Side of Service Engineering pp 510–517Cite as

Discovering Topics of Interest on Steam Community Using an LDA Approach

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 266))

Abstract

Reviews from players regarding different characteristics of an esports game are one of the worthiest sources for the developers to enhance their services or adjust operating strategy. However, little research has been conducted on detecting esports players’ favorite topics dealing with topic modeling. Thus, this paper aims to use a data mining approach to analyze community data in the games domain available on Steam. We collected more than 1.2 million English reviews from four esports games up to August 2020 on Steam. Our contributions in this paper are: (i) we manually build a dataset by filtering out high-quality esports reviews, (ii) we then infer and group reviews into 3 groups with 19 topics, and (iii) we add more contributions to finding the emerging opinions of esports players towards the different topics of esports reviews, which might benefit further research on understanding esports reviews.

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Notes

  1. 1.

    https://www.aesf.com/en/News-And-Media-Coverage/Esports-Returns-As-Proposed-By-The-Hagoc-For-The-2022-Asian-Games.html.

  2. 2.

    https://newzoo.com/insights/trend-reports/newzoo-global-esports-market-report-2020-light-version/.

  3. 3.

    https://store.steampowered.com/.

  4. 4.

    Data available on request from the authors.

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Author information

Authors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Yang Yu, Fangyu Yu & Van-Nam Huynh

  2. Thai Binh Duong University, Nha Trang, Vietnam

    Ba-Hung Nguyen

Authors
  1. Yang Yu
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  2. Ba-Hung Nguyen
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  3. Fangyu Yu
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  4. Van-Nam Huynh
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Corresponding author

Correspondence to Yang Yu .

Editor information

Editors and Affiliations

  1. Centre for Economics and Public Administration, London, UK

    Christine Leitner

  2. Fraunhofer IAO, Stuttgart, Baden-Württemberg, Germany

    Walter Ganz

  3. California State University, Orange, CA, USA

    Debra Satterfield

  4. University of Naples Parthenope, Avellino, Italy

    Clara Bassano

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Yu, Y., Nguyen, BH., Yu, F., Huynh, VN. (2021). Discovering Topics of Interest on Steam Community Using an LDA Approach. In: Leitner, C., Ganz, W., Satterfield, D., Bassano, C. (eds) Advances in the Human Side of Service Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 266. Springer, Cham. https://doi.org/10.1007/978-3-030-80840-2_59

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  • DOI: https://doi.org/10.1007/978-3-030-80840-2_59

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-80839-6

  • Online ISBN: 978-3-030-80840-2

  • eBook Packages: EngineeringEngineering (R0)

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