Measuring social dynamics in a massive multiplayer online game

Abstract

Quantification of human group-behavior has so far defied an empirical, falsifiable approach. This is due to tremendous difficulties in data acquisition of social systems. Massive multiplayer online games (MMOG) provide a fascinating new way of observing hundreds of thousands of simultaneously socially interacting individuals engaged in virtual economic activities. We have compiled a data set consisting of practically all actions of all players over a period of three years from a MMOG played by 300,000 people. This large-scale data set of a socio-economic unit contains all social and economic data from a single and coherent source. Players have to generate a virtual income through economic activities to 'survive' and are typically engaged in a multitude of social activities offered within the game. Our analysis of high-frequency log files focuses on three types of social networks, and tests a series of social-dynamics hypotheses. In particular we study the structure and dynamics of friend-, enemy-and communication networks. We find striking differences in topological structure between positive (friend) and negative (enemy) tie networks. All networks confirm the recently observed phenomenon of network densification. We propose two approximate social laws in communication networks, the first expressing betweenness centrality as the inverse square of the overlap, the second relating communication strength to the cube of the overlap. These empirical laws provide strong quantitative evidence for the Weak ties hypothesis of Granovetter. Further, the analysis of triad significance profiles validates well-established assertions from social balance theory. We find overrepresentation (underrepresentation) of complete (incomplete) triads in networks of positive ties, and vice versa for networks of negative ties. Empirical transition probabilities between triad classes provide evidence for triadic closure with extraordinarily high precision. For the first time we provide empirical results for large-scale networks of negative social ties. Whenever possible we compare our findings with data from non-virtual human groups and provide further evidence that online game communities serve as a valid model for a wide class of human societies.With this setup we demonstrate the feasibility for establishing a 'socio-economic laboratory' which allows to operate at levels of precision approaching those of the natural sciences.All data used in this study is fully anonymized; the authors have the written consent to publish from the legal department of the Medical University of Vienna.

Co-Evolutionary Mechanisms of Emotional Bursts in Online Social Dynamics and Networks

“…Within this approach in the analysis of online social dynamics data, a variety of social networks were observed in relation with different online activities of users [12,15,16,27,30,[52][53][54][55][56]. Here, we use the accepted methods to construct and analyse the networks from the empirical data from Blogs and Chats; we demonstrate that, although in both systems no a priori associations among users exists and the networks grow starting from scratch, the networks that eventually emerge in these processes belong to two entirely different classes of social structures.…”

“…Recently, intensive research based on these empirical data, seen as examples of complex dynamical systems in the physics laboratory, has been performed: this research contributed to quantitative study of social phenomena on Blogs [10,11], Diggs [12], Forums [13], online games [14,15], online social networks MySpace [16], Facebook [17], Twitter [18], online chats [19] and other online communication systems. By using different machine-learning methods of text analysis (a recent review of methods can be found in [20]), one can infer contents that are communicated in the text messages exchanged between users.…”

“…Depending on the interaction mode among users, a specific type of network architecture may appear [10,[14][15][16][26][27][28][29][30]; most of the emergent networks exhibit prevailing characteristics of a social structure;…”

Web Science: Understanding the Emergence of Macro-Level Features on the World Wide Web

“…On other sites, certain actions can be aggregated and used to infer trust and mistrust. For instance, on Wikipedia, editors are promoted within the administrative structure on the basis of an open vote [75], while some multi-player online games also involve decisions to trust fellow players or not [3,339,340].…”

How people make friends in social networking sites—A microscopic perspective

“…Viswanath et al studied the structural evolution of the activity network of Facebook and found that the average degree, clustering coefficient, and average path length are all relatively stable over time [6]. Hu & Wang studied the evolution of Wealink [17,18] and found that many network properties show obvious non-monotone feature, including a sigmoid growth of network scale which was also observed by Chun et al in Cyworld [19], and a transition from degree assortativity characteristic of real social networks to degree disassortativity characteristic of many OSNs which was also observed by Szell & Thurner in Pardus [20].…”