TY - GEN
T1 - Performance dynamics and success in online games
AU - Sapienza, Anna
AU - Peng, Hao
AU - Ferrara, Emilio
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/15
Y1 - 2017/12/15
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85044048832
U2 - 10.1109/ICDMW.2017.124
DO - 10.1109/ICDMW.2017.124
M3 - Conference contribution
AN - SCOPUS:85044048832
T3 - IEEE International Conference on Data Mining Workshops, ICDMW
SP - 902
EP - 909
BT - Proceeding - 17th IEEE International Conference on Data Mining Workshops, ICDMW 2017
A2 - Gottumukkala, Raju
A2 - Karypis, George
A2 - Raghavan, Vijay
A2 - Wu, Xindong
A2 - Miele, Lucio
A2 - Aluru, Srinivas
A2 - Ning, Xia
A2 - Dong, Guozhu
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Data Mining Workshops, ICDMW 2017
Y2 - 18 November 2017 through 21 November 2017
ER -