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A preliminary network analysis on steam game tags: Another way of understanding game genres

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationAcademicMindtrek 2020 - Proceedings of the 23rd International Academic Mindtrek Conference
Subtitle of host publicationJanuary 29-30, 2020, Tampere, Finland
PublisherACM
Pages65-73
Number of pages9
ISBN (Electronic)9781450377744
DOIs
Publication statusPublished - 29 Jan 2020
Publication typeA4 Article in a conference publication
EventAcademic MindTrek Conference - Tampere, Finland
Duration: 29 Jan 202030 Jan 2020

Conference

ConferenceAcademic MindTrek Conference
CountryFinland
CityTampere
Period29/01/2030/01/20

Abstract

Video game genre classification has long been a focusing perspective in game studies domain. Despite the commonly acknowledged usefulness of genre classification, scholars in the game studies domain are yet to reach consensus on the game genre classification. On the other hand, Steam, a popular video game distribution platform, adopts the user-generated tag feature enabling players to describe and annotate video games based on their own understanding of genres. Despite the concern of the quality, the user-generated tags (game tags) provide an opportunity towards an alternative way of understanding video game genres based on the players' collective intelligence. Hence, in this study, we construct a network of game tags based on the co-occurrence of tags in games on Steam platform and analyze the structure of the network via centrality analysis and community detection. Such analysis shall provide an intuitive presentation on the distribution and connections of the game tags, which furthermore suggests a potential way of understanding the important tags that are commonly adopted and the main genres of video games.

Keywords

  • centrality, community detection, game tag, genre, modularity, network, steam, video game

Publication forum classification

Field of science, Statistics Finland