Abstrakti
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.
Alkuperäiskieli | Englanti |
---|---|
Otsikko | DiGRA '20 - Proceedings of the 2020 DiGRA International Conference |
Alaotsikko | Play Everywhere |
Tila | Julkaistu - lokak. 2020 |
OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
Tapahtuma | DiGRA 2020: The 13th Digital Games Research Association Conference: Play Everywhere - Tampere, Suomi Kesto: 2 kesäk. 2020 → 6 kesäk. 2020 Konferenssinumero: 13 https://digra2020.org/ |
Julkaisusarja
Nimi | Conference of Digital Games Research Association |
---|---|
ISSN (elektroninen) | 2342-9666 |
Conference
Conference | DiGRA 2020: The 13th Digital Games Research Association Conference |
---|---|
Maa/Alue | Suomi |
Kaupunki | Tampere |
Ajanjakso | 2/06/20 → 6/06/20 |
www-osoite |
Julkaisufoorumi-taso
- Jufo-taso 1