A Data-Driven Approach for Game Evaluation Using Latent Dirichlet Allocation Method Based on Players’ Reviews

Authors

  • Muhammad Rizky Anditama Universitas Indonesia
  • Nadhirsyah
  • Robby Hermansyah
  • Achmad Nizar Hidayanto

DOI:

https://doi.org/10.21609/jsi.v20i2.1429

Keywords:

LDA, Garena, Data Mining, Gameplay, Free Fire, Google Play, Review, Topic Modelling

Abstract

Garena is a global game developer and publisher. Garena provides users with access to popular and engaging online games for mobile and PC, developed, curated, and localized for each market. The Battle Royale genre is relatively new, and this research will evaluate Free Fire, one of the games in this genre made by Garena. Analyzing end-user reviews is considered important for evaluating software quality. Researchers need to understand which aspects need to be evaluated based on player reviews on Google Play and how the model's performance is generated using feedback from players who have played Free Fire. In this study, researchers use the Latent Dirichlet Allocation (LDA) method to model topics and generate clusters in discussions for each topic. LDA is a generative probabilistic model of a corpus. This research on topic modeling using Google Play reviews and LDA has identified the topics users are most concerned with. The research shows three main aspects: bugs, graphics and performance, and game rules/punishment policy, as aspects that need to be evaluated based on player reviews on Google Play.

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Published

2024-10-11

How to Cite

Muhammad Rizky Anditama, Robby Hermansyah, Robby Hermansyah, & Achmad Nizar Hidayanto. (2024). A Data-Driven Approach for Game Evaluation Using Latent Dirichlet Allocation Method Based on Players’ Reviews. Jurnal Sistem Informasi, 20(2), 68–77. https://doi.org/10.21609/jsi.v20i2.1429

Issue

Vol. 20 No. 2 (2024): Jurnal Sistem Informasi (Journal of Information System)

Section

Articles

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