https://doi.org/10.21697/kmt.2023.54.02
Article presents research conducted on best-selling games offered on Steam. The aim of research was to deliver description of player’s identity focused on the outcomes of those games reviews and its reviewers metadata analysis. In order to achieve it, firstly author downloaded both game reviews and metadata within Steam API using his python script and python module steamreviews 0.9.5. Secondly, author prepared an own set of research tools – representameter, review selector and playermeter – he used for performing analysis on downloaded data. The research proved solid enough to indicate some specific data about player’s identity: involvement in Steam activities, sort of preferred activities, most frequently chosen video game genres, way of structuring the narrative in video game reviews.
Język Polski
English