2017 IEEE International Conference on Data Mining Workshops (ICDMW) (2017)
New Orleans, Louisiana, USA
Nov. 18, 2017 to Nov. 21, 2017
Online data provide a way to monitor how users behave in social systems like social networks and online games, and understand which features turn an ordinary individual into a successful one. Here, we propose to study individual performance and success in Multiplayer Online Battle Arena (MOBA) games. Our purpose is to identify those behaviors and playing styles that are characteristic of players with high skill level and that distinguish them from other players. To this aim, we study Defense of the ancient 2 (Dota 2), a popular MOBA game. Our findings highlight three main aspects to be successful in the game: (i) players need to have a warm-up period to enhance their performance in the game; (ii) having a long in-game experience does not necessarily translate in achieving better skills; but rather, (iii) players that reach high skill levels differentiate from others because of their aggressive playing strategy, which implies to kill opponents more often than cooperating with teammates, and trying to give an early end to the match.
computer games, data analysis, social networking (online)
A. Sapienza, H. Peng and E. Ferrara, "Performance Dynamics and Success in Online Games," 2017 IEEE International Conference on Data Mining Workshops (ICDMW), New Orleans, Louisiana, USA, 2018, pp. 902-909.