Julian Runge

2papers

2 Papers

HCDec 7, 2016
Play With Me? Understanding and Measuring the Social Aspect of Casual Gaming

Adam Alsén, Julian Runge, Anders Drachen et al.

Social gaming is today a pervasive phenomenon. Driven by the advent of social networks and the digitization of game distribution. In this paper the impact of digitization and so-cial networks such as Facebook on digital games is de-scribed and evaluated. This impact follows several vectors, including the introduction of new game formats and extend-ing the traditional audiences for games, which in turn has increased industrial revenue. The industry is in turn shaped by new business model such as Free-to-Play, digital distri-bution and the use of viral social features. These changes do not only appear irreversible, but more importantly, play a part in shaping the future of digital game design, notably for mobile devices. The paper presents new knowledge from controlled live experiments from a casual social game across Facebook and mobile platforms, finding positive re-turns by adding social gameplay features. This suggests that not only social network games, but also casual mobile games can benefit from deeper social gameplay mechanics. Given the impact of social features on gameplay, Game An-alytics will need to evolve to be able to handle requirements that arise from the introduction of social features, e.g. how to measure engagement against social features and shaping organic and viral spreading of a game.

MLJul 12, 2016
Rapid Prediction of Player Retention in Free-to-Play Mobile Games

Anders Drachen, Eric Thurston Lundquist, Yungjen Kung et al.

Predicting and improving player retention is crucial to the success of mobile Free-to-Play games. This paper explores the problem of rapid retention prediction in this context. Heuristic modeling approaches are introduced as a way of building simple rules for predicting short-term retention. Compared to common classification algorithms, our heuristic-based approach achieves reasonable and comparable performance using information from the first session, day, and week of player activity.