Abstract
The availability of big data recorded from massively multiplayer online role-playing games (MMORPGs) allows us to gain a deeper understanding of the potential connection between individuals’ network positions and their economic outputs. We use a statistical filtering method to construct dependence networks from weighted friendship networks of individuals. We investigate the 30 distinct motif positions in the 13 directed triadic motifs which represent microscopic dependences among individuals. Based on the structural similarity of motif positions, we further classify individuals into different groups. The node position diversity of individuals is found to be positively correlated with their economic outputs. We also find that the economic outputs of leaf nodes are significantly lower than that of the other nodes in the same motif. Our findings shed light on understanding the influence of network structure on economic activities and outputs in socioeconomic systems.
Highlights
Considerable studies have offered us a deep understanding of the influence of network structures on the dynamics of complex systems, such as the spreading of diseases and information [ ] and emerging of collaborations [ ]
Our results indicate that the individuals who appear in more triadic motif positions have higher economic outputs
4 Discussion In this paper we analyzed the relationship between friendship structure and economic output for individuals in a massively multiplayer online role-playing game
Summary
Considerable studies have offered us a deep understanding of the influence of network structures on the dynamics of complex systems, such as the spreading of diseases and information [ ] and emerging of collaborations [ ]. The connection between network position and economic output is less studied. Eagle et al argue that the diversity of individual relationships within a community strongly correlates with economic development of communities [ ]. Similar to the friendship networks of US students [ ], Xie et al studied triadic motifs in dependence networks of virtual societies and found that low level individuals have preference of forming links to high level individuals [ ]. Their findings in virtual world are consistent with empirical findings in real society that ‘collaboration is easier when both
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