EPJ Data Sci. (2019) 8: 22
https://doi.org/10.1140/epjds/s13688-019-0200-1

Regular article

The dynamics of collective social behavior in a crowd controlled game

¹ Institute for Biocomputation and Physics of Complex Systems, University of Zaragoza, Zaragoza, Spain
² Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
³ ISI Foundation, Turin, Italy

^* e-mail: albertoaleta@gmail.com

Received: 25 January 2019
Accepted: 30 May 2019
Published online: 7 June 2019

Abstract

Despite many efforts, the behavior of a crowd is not fully understood. The advent of modern communication means has made it an even more challenging problem, as crowd dynamics could be driven by both human-to-human and human-technology interactions. Here, we study the dynamics of a crowd controlled game (Twitch Plays Pokémon), in which nearly a million players participated during more than two weeks. Unlike other online games, in this event all the players controlled exactly the same character and thus it represents an exceptional example of a collective mind working to achieve a certain goal. We dissect the temporal evolution of the system dynamics along the two distinct phases that characterized the game. We find that having a fraction of players who do not follow the crowd’s average behavior is key to succeed in the game. The latter finding can be well explained by an nth order Markov model that reproduces the observed behavior. Secondly, we analyze a phase of the game in which players were able to decide between two different modes of playing, mimicking a voting system. We show that the introduction of this system clearly polarized the community, splitting it in two. Finally, we discuss one of the peculiarities of these groups in the light of the social identity theory, which appears to describe well some of the observed dynamics.