Multirelational organization of large-scale social networks in an online world

By Michael Szell, Renaud Lambiotte, Stefan Thurner 4. Proceedings of the National Academy of Sciences of the United States of America, 2010

882 citations recorded by the source corpus.

The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a nonlinear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multidimensional nature of these interactions has largely been ignored, mostly because of lack of data. Here, for the first time, we analyze a complete, multirelational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering, and fatter-tail degree distribution. We then explore how the interdependence of different network types determines the organization of the social system. In particular, we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach, we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/350bdb162f1a02791db10ad887b84fdf231c92e5

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Citations in the corpus

The structure and dynamics of multilayer networks (2014, methodology): “Overlap and multidegree A large variety of data sets, including the multiplex airport network, on-line social games, collaboration and citation networks [63,78,113], display a significant overlap of the links.”
A Survey of Signed Network Mining in Social Media (2015, background): “This suggests that many useful properties such as triadic closure cannot be applied to negative links [Szell et al. 2010].”
Structural balance in the social networks of a wild mammal (2013, methodology): “Weak, or generalized, structural balance is empirically more common than strong (regular) structural balance in human social networks (Leskovec et al. 2010; van de Rijt 2011), although recently, strong structural balance was demonstrated in a large human online network (Szell et al. 2010).”
Latent Space Model for Multi-Modal Social Data (2015, background): “However, a number of recent studies makes it increasingly clear that focusing only on network properties while discarding rich contextual information limits our comprehensive understanding of complex social systems dynamics [52, 36, 4, 56, 18, 32, 49, 37, 20, 25, 27, 2].”
Multilayer networks (2013, background): “, different edge labels) represent different types of social relationships [4, 201, 328, 350].”
Navigability of interconnected networks under random failures (2013, background): “Recently, progress has been made to include such levels in network analysis within the more general framework of interconnected networks (12, 39), accounting for the influence of their topologies and their interconnections to dynamical processes taking place on the networked system (3, 4).”
Computing global structural balance in large-scale signed social networks (2011, background): “Partial hints that social networks currently available are more balanced than expected are provided by both the small motif scre ening of [13, 1] and the spectral analysis of [18], and are confirmed by our analysis.”
Measuring Large-Scale Social Networks with High Resolution (2014, background): “While recent work [114,115] begin to explore the topic, a coherent theory describing multiplex, weighted, and directed networks remains beyond the frontier of our current understanding.”
Friends and Foes: The dynamics of dual social structures (2014, methodology): “First, to evaluate the expected rate of formation of a given type of dyad or triad from year t to t 1, we simulated a random network with the same size and degree distribution as the observed network in year t 1 (Szell et al., 2010).”
Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games (2015, background): “These rich electronic footprints enable and encourage research of social dynamics [22, 28, 47].”
Complex systems: physics beyond physics (2016, neutral): “In the particular case of the Pardus.at game ﬁrst steps were taken in this direction in [53, 54, 66–74].”
Link Prediction in Complex Networks: A Survey (2010, background): “Recent development of social balance theory may provide useful hints [156,157,158].”
The “online brain”: how the Internet may be changing our cognition (2019, background): “…for self esteem can have adverse effects on young people, particularly those with low socialemotional wellbeing, due to high rates of cyberbullying 108 increased anxiety and depression 109,110 and increased perceptions of social isolation and exclusion among those who feel rejected online 111 .”