Trust- and reputation-based opinion dynamics modelling over temporal networks

IF 2.2 4区数学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Journal of complex networks Pub Date : 2022-07-01 DOI:10.1093/comnet/cnac019

Eeti Jain;Anurag Singh;Ernesto Estrada

引用次数: 2

Abstract

Trust and reputation are a person's belief over another person and are essential factors while opinion values are shared among online social platforms. Both the values are calculated using past shared opinions and the structure of the network. Further, a credibility score is calculated using the trust and reputation of the nodes, which is helpful to share the opinion values more accurately. In this work, an opinion dynamics temporal network is modelled using the credibility score of the nodes in the network. The addition and deletion of the edges and the opinion evolution occur on the basis of the credibility score of the nodes. Results are analysed over scale-free networks generated using Bollabas et al. model. Such scale-free networks are evolved over time termed as temporal network using the proposed model. It is analysed how the different threshold values on the credibility score of the nodes affect the opinion values convergence on the proposed model.

查看原文本刊更多论文

基于信任和声誉的意见动态建模的时间网络

信任和声誉是一个人对另一个人的信念，也是在线社交平台之间共享意见价值观的重要因素。这两个值都是使用过去的共同意见和网络结构计算的。此外，使用节点的信任和信誉来计算可信度得分，这有助于更准确地共享意见值。在这项工作中，使用网络中节点的可信度分数对意见动态时间网络进行建模。边缘的添加和删除以及意见的演变是基于节点的可信度得分进行的。通过使用Bollabas等人的模型生成的无标度网络来分析结果。使用所提出的模型，这种无标度网络随着时间的推移而演变，称为时间网络。分析了节点可信度得分的不同阈值如何影响所提出模型的意见值收敛。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of complex networks MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-

CiteScore

4.20

自引率

9.50%

发文量

期刊介绍： Journal of Complex Networks publishes original articles and reviews with a significant contribution to the analysis and understanding of complex networks and its applications in diverse fields. Complex networks are loosely defined as networks with nontrivial topology and dynamics, which appear as the skeletons of complex systems in the real-world. The journal covers everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications leading to predictive models in molecular, biological, ecological, informational, engineering, social, technological and other systems. It includes, but is not limited to, the following topics: - Mathematical and numerical analysis of networks - Network theory and computer sciences - Structural analysis of networks - Dynamics on networks - Physical models on networks - Networks and epidemiology - Social, socio-economic and political networks - Ecological networks - Technological and infrastructural networks - Brain and tissue networks - Biological and molecular networks - Spatial networks - Techno-social networks i.e. online social networks, social networking sites, social media - Other applications of networks - Evolving networks - Multilayer networks - Game theory on networks - Biomedicine related networks - Animal social networks - Climate networks - Cognitive, language and informational network