A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews
Playability is a key concept in game studies defining the overall quality of video games. Although its definition and frameworks are widely studied, methods to analyze and evaluate the playability of video games are still limited. Using heuristics for playability evaluation has long been the mainstr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/12/3/129 |
| _version_ | 1797540997079498752 |
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| author | Xiaozhou Li Zheying Zhang Kostas Stefanidis |
| author_facet | Xiaozhou Li Zheying Zhang Kostas Stefanidis |
| author_sort | Xiaozhou Li |
| collection | DOAJ |
| description | Playability is a key concept in game studies defining the overall quality of video games. Although its definition and frameworks are widely studied, methods to analyze and evaluate the playability of video games are still limited. Using heuristics for playability evaluation has long been the mainstream with its usefulness in detecting playability issues during game development well acknowledged. However, such a method falls short in evaluating the overall playability of video games as published software products and understanding the genuine needs of players. Thus, this paper proposes an approach to analyze the playability of video games by mining a large number of players’ opinions from their reviews. Guided by the game-as-system definition of playability, the approach is a data mining pipeline where sentiment analysis, binary classification, multi-label text classification, and topic modeling are sequentially performed. We also conducted a case study on a particular video game product with its 99,993 player reviews on the Steam platform. The results show that such a review-data-driven method can effectively evaluate the perceived quality of video games and enumerate their merits and defects in terms of playability. |
| first_indexed | 2024-03-10T13:09:00Z |
| format | Article |
| id | doaj.art-c6943f88a7934918b6c740c0e24859e6 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-10T13:09:00Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-c6943f88a7934918b6c740c0e24859e62023-11-21T10:54:57ZengMDPI AGInformation2078-24892021-03-0112312910.3390/info12030129A Data-Driven Approach for Video Game Playability Analysis Based on Players’ ReviewsXiaozhou Li0Zheying Zhang1Kostas Stefanidis2Faculty of Information Technology and Communication Sciences, Tampere University, Kalevantie 4, 33100 Tampere, FinlandFaculty of Information Technology and Communication Sciences, Tampere University, Kalevantie 4, 33100 Tampere, FinlandFaculty of Information Technology and Communication Sciences, Tampere University, Kalevantie 4, 33100 Tampere, FinlandPlayability is a key concept in game studies defining the overall quality of video games. Although its definition and frameworks are widely studied, methods to analyze and evaluate the playability of video games are still limited. Using heuristics for playability evaluation has long been the mainstream with its usefulness in detecting playability issues during game development well acknowledged. However, such a method falls short in evaluating the overall playability of video games as published software products and understanding the genuine needs of players. Thus, this paper proposes an approach to analyze the playability of video games by mining a large number of players’ opinions from their reviews. Guided by the game-as-system definition of playability, the approach is a data mining pipeline where sentiment analysis, binary classification, multi-label text classification, and topic modeling are sequentially performed. We also conducted a case study on a particular video game product with its 99,993 player reviews on the Steam platform. The results show that such a review-data-driven method can effectively evaluate the perceived quality of video games and enumerate their merits and defects in terms of playability.https://www.mdpi.com/2078-2489/12/3/129playabilityplayer reviewstext classificationsentiment analysistopic modelingsteam |
| spellingShingle | Xiaozhou Li Zheying Zhang Kostas Stefanidis A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews Information playability player reviews text classification sentiment analysis topic modeling steam |
| title | A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews |
| title_full | A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews |
| title_fullStr | A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews |
| title_full_unstemmed | A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews |
| title_short | A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews |
| title_sort | data driven approach for video game playability analysis based on players reviews |
| topic | playability player reviews text classification sentiment analysis topic modeling steam |
| url | https://www.mdpi.com/2078-2489/12/3/129 |
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