Modeling communication asymmetry and content personalization in online social networks

Q1 Social Sciences Online Social Networks and Media Pub Date : 2023-09-01 DOI:10.1016/j.osnem.2023.100269
Franco Galante , Luca Vassio , Michele Garetto , Emilio Leonardi
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引用次数: 0

Abstract

The increasing popularity of online social networks (OSNs) attracted growing interest in modeling social interactions. On online social platforms, a few individuals, commonly referred to as influencers, produce the majority of content consumed by users and hegemonize the landscape of the social debate. However, classical opinion models do not capture this communication asymmetry. We develop an opinion model inspired by observations on social media platforms with two main objectives: first, to describe this inherent communication asymmetry in OSNs, and second, to model the effects of content personalization. We derive a Fokker–Planck equation for the temporal evolution of users’ opinion distribution and analytically characterize the stationary system behavior. Analytical results, confirmed by Monte-Carlo simulations, show how strict forms of content personalization tend to radicalize user opinion, leading to the emergence of echo chambers, and favor structurally advantaged influencers. As an example application, we apply our model to Facebook data during the Italian government crisis in 2019. Our work provides a flexible framework to evaluate the impact of content personalization on the opinion formation process, focusing on the interaction between influential individuals and regular users. This framework is interesting in the context of marketing and advertising, misinformation spreading, politics and activism.

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在线社交网络中的传播不对称与内容个性化建模
在线社交网络(OSN)的日益流行吸引了人们对社交互动建模的兴趣。在在线社交平台上,少数人,通常被称为影响者,产生了用户消费的大部分内容,并主导了社会辩论的格局。然而,经典的意见模型并没有捕捉到这种沟通不对称。我们根据社交媒体平台上的观察结果开发了一个观点模型,其主要目的有两个:第一,描述OSN中固有的沟通不对称,第二,对内容个性化的影响进行建模。我们推导了用户意见分布的时间演化的Fokker–Planck方程,并分析了平稳系统行为的特征。蒙特卡洛模拟证实的分析结果表明,严格形式的内容个性化往往会激进化用户意见,导致回音室的出现,并有利于结构优势的影响者。作为一个示例应用程序,我们将我们的模型应用于2019年意大利政府危机期间的Facebook数据。我们的工作提供了一个灵活的框架来评估内容个性化对意见形成过程的影响,重点关注有影响力的个人和普通用户之间的互动。这个框架在营销和广告、错误信息传播、政治和激进主义的背景下很有趣。
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来源期刊
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
期刊最新文献
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