Understanding how retweets influence the behaviors of social networking service users via agent-based simulation

Q1 Mathematics
Yan, Yizhou, Toriumi, Fujio, Sugawara, Toshiharu
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引用次数: 5

Abstract

The retweet is a characteristic mechanism of several social network services/social media, such as Facebook, Twitter, and Weibo. By retweeting tweet, users can share an article with their friends and followers. However, it is not clear how retweets affect the dominant behaviors of users. Therefore, this study investigates the impact of retweets on the behavior of social media users from the perspective of networked game theory, and how the existence of the retweet mechanism in social media promotes or reduces the willingness of users to post and comment on articles. To address these issues, we propose the retweet reward game model and quote tweet reward game model by adding the retweet and quote tweet mechanisms to a relatively simple social networking service model known as the reward game. Subsequently, we conduct simulation-based experiments to understand the influence of retweets on the user behavior on various networks. It is demonstrated that users will be more willing to post new articles with a retweet mechanism, and quote retweets are more beneficial to users, as users can expect to spread their information and their own comments on already posted articles.
通过基于代理的模拟了解转发如何影响社交网络服务用户的行为
转发是一些社交网络服务/社交媒体的特征机制,如Facebook、Twitter和微博。通过转发,用户可以与他们的朋友和追随者分享一篇文章。然而,目前尚不清楚转发如何影响用户的主导行为。因此,本研究从网络博弈论的角度考察了转发对社交媒体用户行为的影响,以及社交媒体中转发机制的存在是如何促进或降低用户发布和评论文章的意愿的。为了解决这些问题,我们提出了转发奖励游戏模型和引用tweet奖励游戏模型,通过将转发和引用tweet机制添加到一个相对简单的社交网络服务模型中,即奖励游戏。随后,我们进行了基于模拟的实验,以了解各种网络上的转发对用户行为的影响。研究表明,有了转发机制,用户会更愿意发布新的文章,而引用转发对用户更有利,因为用户可以期望传播自己的信息和自己对已经发布的文章的评论。
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
Computational Social Networks Mathematics-Modeling and Simulation
自引率
0.00%
发文量
0
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.
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