基于多元Hawkes过程量化Twitter上用户行为对假新闻传播的影响
Quantifying the Influence of User Behaviors on the Dissemination of Fake News on Twitter with Multivariate Hawkes Processes
AI总结：
本研究针对Twitter平台假新闻传播问题，提出融合用户网络、推文类型、用户立场的多元Hawkes点过程模型，量化用户行为对假新闻传播的影响，为虚假信息传播干预提供支撑。
摘要：
假新闻已成为在线社交网络中普遍存在的问题，引发了该领域的研究热潮。理解假新闻的传播机制，对于认清在线社交网络中虚假/错误信息的传播规律及其对用户的影响至关重要。这类认知有助于制定干预措施以遏制虚假信息扩散，并提醒受影响用户对欺诈性/恶意内容保持警惕。本文针对Twitter平台，提出一种多元Hawkes点过程模型，将用户网络、响应推文类型、用户立场等关键因素作为模型参数，旨在探究并量化这些因素对假新闻传播过程的影响。我们利用Expectation Maximization（期望最大化）算法推导了参数估计表达式，并在模拟数据集上验证了其有效性。此外，我们使用从Twitter收集的真实假新闻数据集开展案例研究，探究用户立场与推文类型对传播模式的影响。该分析为理解用户如何受虚假/错误信息传播过程影响、又如何作用于该过程提供了宝贵见解，同时证明了我们的模型可助力对该过程进行干预。
英文摘要：
Fake news has emerged as a pervasive problem within Online Social Networks, leading to a surge of research interest in this area. Understanding the dissemination mechanisms of fake news is crucial in comprehending the propagation of disinformation/misinformation and its impact on users in Online Social Networks. This knowledge can facilitate the development of interventions to curtail the spread of false information and inform affected users to remain vigilant against fraudulent/malicious content. In this paper, we specifically target the Twitter platform and propose a Multivariate Hawkes Point Processes model that incorporates essential factors such as user networks, response tweet types, and user stances as model parameters. Our objective is to investigate and quantify their influence on the dissemination process of fake news. We derive parameter estimation expressions using an Expectation Maximization algorithm and validate them on a simulated dataset. Furthermore, we conduct a case study using a real dataset of fake news collected from Twitter to explore the impact of user stances and tweet types on dissemination patterns. This analysis provides valuable insights into how users are influenced by or influence the dissemination process of disinformation/misinformation, and demonstrates how our model can aid in intervening in this process.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
