Consensus dynamics in online collaboration systems.

Q1 Mathematics

Computational Social Networks Pub Date : 2018-01-01 Epub Date: 2018-02-01 DOI:10.1186/s40649-018-0050-1

Ilire Hasani-Mavriqi, Dominik Kowald, Denis Helic, Elisabeth Lex

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Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: In summary, our results suggest that achieving an optimal consensus building process in collaboration systems requires an appropriate balance between those two factors.

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在线协作系统中的共识动态。

背景：在本文中，我们研究了在线协作系统中的意见动态和共识建立过程，在该系统中，用户根据他们的共同兴趣和社会地位进行互动。具体来说，我们感兴趣的是用户的相似性和他们在社区中的社会地位，以及这两个因素的相互作用如何影响共识的动态过程：在我们的研究中，我们使用著名的命名游戏模型模拟协作系统中的意见扩散，并通过纳入基于用户相似性和用户社会地位的互动机制对该模型进行了扩展。我们在从网络中提取的协作数据集上进行了实验：我们的研究结果表明，当用户以其与其他用户的相似性为导向时，在线协作系统中建立共识的过程就会延迟。适当提高用户社会地位对其行为的影响反过来又能促进这一进程：总之，我们的研究结果表明，要在协作系统中实现建立共识的最佳过程，需要在这两个因素之间取得适当的平衡。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational Social Networks Mathematics-Modeling and Simulation

自引率

0.00%

发文量

审稿时长

13 weeks

期刊介绍： Computational Social Networks showcases refereed papers dealing with all mathematical, computational and applied aspects of social computing. The objective of this journal is to advance and promote the theoretical foundation, mathematical aspects, and applications of social computing. Submissions are welcome which focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media. Topics include (but are not limited to) the following: -Social network design and architecture -Mathematical modeling and analysis -Real-world complex networks -Information retrieval in social contexts, political analysts -Network structure analysis -Network dynamics optimization -Complex network robustness and vulnerability -Information diffusion models and analysis -Security and privacy -Searching in complex networks -Efficient algorithms -Network behaviors -Trust and reputation -Social Influence -Social Recommendation -Social media analysis -Big data analysis on online social networks This journal publishes rigorously refereed papers dealing with all mathematical, computational and applied aspects of social computing. The journal also includes reviews of appropriate books as special issues on hot topics.