Abstract
Current game publishing typically involves an ongoing commitment to maintain and update games after initial release, and as a result the reception of games among players has the potential to evolve; it is then crucial to understand how players’ concerns and perception of the game are affected by ongoing updates and by passage of time in general. We carry out a data-driven analysis of a prominent game release, No Man’s Sky, using topic modeling based text mining of Steam reviews. Importantly, our approach treats player perception not as a single sentiment but identifies multiple topics of interest that evolve differently over time, and allows us to contrast patching of the game to evolution of the topics.
| Original language | English |
|---|---|
| Title of host publication | DiGRA '20 - Proceedings of the 2020 DiGRA International Conference |
| Subtitle of host publication | Play Everywhere |
| Publisher | DiGRA |
| Publication status | Published - Oct 2020 |
| Publication type | A4 Article in conference proceedings |
| Event | DiGRA 2020: The 13th Digital Games Research Association Conference: Play Everywhere - Tampere, Finland Duration: 2 Jun 2020 → 6 Jun 2020 Conference number: 13 https://digra2020.org/ |
Publication series
| Name | Conference of Digital Games Research Association |
|---|---|
| ISSN (Electronic) | 2342-9666 |
Conference
| Conference | DiGRA 2020: The 13th Digital Games Research Association Conference |
|---|---|
| Country/Territory | Finland |
| City | Tampere |
| Period | 2/06/20 → 6/06/20 |
| Internet address |
Publication forum classification
- Publication forum level 1