@article{Egliston_2016, title={Big playerbase, big data: On data analytics methodologies and their applicability to studying multiplayer games and culture}, volume={21}, url={https://firstmonday.org/ojs/index.php/fm/article/view/6718}, DOI={10.5210/fm.v21i7.6718}, abstractNote={<p>Rapport with big data is something of a methodological rarity in empirical work on videogames, particularly within humanities oriented literature; an unusual omission considering the scope of many multiplayer game environments. Addressing this, the present work ventures the question ‘how can research into multiplayer videogames benefit from the use of big data’? I offer a response through a case study of Valve Software’s multiplayer game Dota 2, presenting a number of approaches which draw on player data analytics. In addition to mapping out frameworks for empirical research, I explore the theoretical dimensions of porting analytics based approaches to studies of multiplayer videogames, charting perceived incompatibilities between analytics approaches and popular ontologies of play, and how the prevalence of relational ontologies of play privilege particular modes of empirical inquiry.</p>}, number={7}, journal={First Monday}, author={Egliston, Ben}, year={2016}, month={Jun.} }