Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2016

Hasani-Mavriqi Ilire, Geigl Florian, Pujari Subhash Chandra , Lex Elisabeth, Helic Denis

The Influence of Social Status and Network Structure on Consensus Building in Collaboration Networks

Social Network Analysis and Mining, Reda Alhajj, Springer Vienna, 2016

Journal
In this paper, we study the process of opinion dynamics and consensus building in online collaboration systems, in which users interact with each other following their common interests and their social profiles. Specifically, we are interested in how users similarity and their social status in the community, as well as the interplay of those two factors influence the process of consensus dynamics. For our study, we simulate the diffusion of opinions in collaboration systems using the well-known Naming Game model, which we extend by incorporating an interaction mechanism based on user similarity and user social status. We conduct our experiments on collaborative datasets extracted from the Web. Our findings reveal that when users are guided by their similarity to other users, the process of consensus building in online collaboration systems is delayed. A suitable increase of influence of user social status on their actions can in turn facilitate this process. In summary, our results suggest that achieving an optimal consensus building process in collaboration systems requires an appropriate balance between those two factors.
2015

Hasani-Mavriqi Ilire, Geigl Florian, Pujari Subhash Chandra, Lex Elisabeth, Helic Denis

Influence of Status Social on Consensus Building in Collaboration Networks

In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), Jian Pei, Fabrizio Silvestri and Jie Tang, ACM/IEEE, Paris, France, 2015

Konferenz
In this paper, we analyze the influence of social status on opinion dynamics and consensus building in collaboration networks. To that end, we simulate the diffusion of opinions in empirical collaboration networks by taking into account both the network structure and the individual differences of people reflected through their social status. For our simulations, we adapt a well-known Naming Game model and extend it with the Probabilistic Meeting Rule to account for the social status of individuals participating in a meeting. This mechanism is sufficiently flexible and allows us to model various situations in collaboration networks, such as the emergence or disappearance of social classes. In this work, we concentrate on studying three well-known forms of class society: egalitarian, ranked and stratified. In particular, we are interested in the way these society forms facilitate opinion diffusion. Our experimental findings reveal that (i) opinion dynamics in collaboration networks is indeed affected by the individuals’ social status and (ii) this effect is intricate and non-obvious. In particular, although the social status favors consensus building, relying on it too strongly can slow down the opinion diffusion, indicating that there is a specific setting for each collaboration network in which social status optimally benefits the consensus building process.
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