论文标题
一个基于病毒营销的模型,用于在线社交网络中的意见动态
A Viral Marketing-Based Model For Opinion Dynamics in Online Social Networks
论文作者
论文摘要
在线社交网络为公民提供了关于不同社会问题的意见,并为公众讨论提供了意见。他们还使用户接触病毒含量,例如打破新闻文章。在本文中,我们研究了这两个方面之间的相互作用:在线社交网络中的意见形成和信息级联。我们提出了一个新模型,该模型使我们能够在接触病毒内容时如何量化用户改变意见。我们的模型是流行的Friedkin-Johnsen模型的意见动力学模型和信息传播的独立级联模型。我们提出了用于模拟我们的模型的算法,并提供了近似算法以优化某些网络索引,例如用户意见的总和或分歧 - 争辩索引;我们的方法可以用来获得有关在线社交网络中增加这些索引多少这些索引的见解。最后,我们在现实世界数据集上评估了我们的模型。我们在实验上表明,营销活动和两极分化的内容对网络的影响差异很大:虽然前者对网络的两极分化的影响有限,但即使只有0.5%的用户开始共享两极分化的内容,后者也可以将极化提高到59%。我们认为,这一发现对当今的在线媒体中日益增长的种族隔离有所了解。
Online social networks provide a medium for citizens to form opinions on different societal issues, and a forum for public discussion. They also expose users to viral content, such as breaking news articles. In this paper, we study the interplay between these two aspects: opinion formation and information cascades in online social networks. We present a new model that allows us to quantify how users change their opinion as they are exposed to viral content. Our model is a combination of the popular Friedkin--Johnsen model for opinion dynamics and the independent cascade model for information propagation. We present algorithms for simulating our model, and we provide approximation algorithms for optimizing certain network indices, such as the sum of user opinions or the disagreement--controversy index; our approach can be used to obtain insights into how much viral content can increase these indices in online social networks. Finally, we evaluate our model on real-world datasets. We show experimentally that marketing campaigns and polarizing contents have vastly different effects on the network: while the former have only limited effect on the polarization in the network, the latter can increase the polarization up to 59% even when only 0.5% of the users start sharing a polarizing content. We believe that this finding sheds some light into the growing segregation in today's online media.