"This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders

Assessing Individual and Community Vulnerability to Fake News in Social Networks

The plague of false information, popularly called fake news has affected lives of news consumers ever since the prevalence of social media. Thus understanding the spread of false information in social networks has gained a lot of attention in the literature. While most proposed models do content analysis of the information, no much work has been done by exploring the community structures that also play an important role in determining how people get exposed to it. In this paper we base our idea on Computational Trust in social networks to propose a novel Community Health Assessment model again…

一种用于假新闻传播的随机ISCS马尔可夫模型

A Stochastic ISCS Markov Model for Fake News Propagation

提出基于马尔可夫链的随机谣言传播模型，引入事实核查者分析其对假新闻动态的影响，并通过数值模拟验证。

逐步欺骗：使用LLM智能体模拟从真实新闻到假新闻的演化

The Stepwise Deception: Simulating the Evolution from True News to Fake News with LLM Agents

提出基于LLM智能体的FUSE框架，模拟真实新闻在社交互动中逐步扭曲为假新闻的演化过程，并开发FUSE-EVAL评估真相偏差，实验证明其能有效重现假新闻演化场景并支持早期干预。

Competitive Influence Propagation and Fake News Mitigation in the Presence of Strong User Bias

Due to the extensive role of social networks in social media, it is easy for people to share the news, and it spreads faster than ever before. These platforms also have been exploited to share the rumor or fake information, which is a threat to society. One method to reduce the impact of fake information is making people aware of the correct information based on hard proof. In this work, first, we propose a propagation model called Competitive Independent Cascade Model with users' Bias (CICMB) that considers the presence of strong user bias towards different opinions, believes, or political pa…

解码虚假信息传播者的新闻媒体饮食结构

Decoding the News Media Diet of Disinformation Spreaders

本研究运用网络科学和熵测度分析社交媒体用户新闻消费行为，发现虚假信息传播者的新闻消费模式与普通用户存在显著差异，其域名选择更多样且更规律，为制定更有效的社交媒体审核政策提供依据。

社交媒体中假新闻的分享与传播建模

Modeling The Sharing and Diffusion Of Fake News in Social Media

本文融合用户属性、主题兴趣、关系强度及新闻复杂性、文体与心理特征建模，利用机器学习识别假新闻分享者并预测传播，发现有影响力用户分享的新闻更易扩散。

Combating fake news by empowering fact-checked news spread via topology-based interventions

Rapid information diffusion and large-scaled information cascades can enable the undesired spread of false information. A small-scaled false information outbreak may potentially lead to an infodemic. We propose a novel information diffusion and intervention technique to combat the spread of false news. As false information is often spreading faster in a social network, the proposed diffusion methodology inhibits the spread of false news by proactively diffusing the fact-checked information. Our methodology mainly relies on defining the potential super-spreaders in a social network based on the…

Influence maximization in noisy networks

We consider the problem of identifying the most influential nodes for a spreading process on a network when prior knowledge about structure and dynamics of the system is incomplete or erroneous. Specifically, we perform a numerical analysis where the set of top spreaders is determined on the basis of prior information that is artificially altered by a certain level of noise. We then measure the optimality of the chosen set by measuring its spreading impact in the true system. Whereas we find that the identification of top spreaders is optimal when prior knowledge is complete and free of mistak…

The Fake News Spreading Plague: Was it Preventable?

In 2010, a paper entitled "From Obscurity to Prominence in Minutes: Political Speech and Real-time search" won the Best Paper Prize of the Web Science 2010 Conference. Among its findings were the discovery and documentation of what was termed a "Twitter-bomb", an organized effort to spread misinformation about the democratic candidate Martha Coakley through anonymous Twitter accounts. In this paper, after summarizing the details of that event, we outline the recipe of how social networks are used to spread misinformation. One of the most important steps in such a recipe is the "infiltration" o…

在现实环境中识别假新闻网站

Finding Fake News Websites in the Wild

针对虚假信息网站名单获取困难的问题，本研究提出一种通过关联社交媒体上分享经证实假新闻的用户来识别虚假信息网站的新方法，经Twitter多模式验证有效，可助力相关研究与治理。

Spatial Games of Fake News

To curb the spread of fake news on social media platforms, recent studies have considered an online crowdsourcing fact-checking approach as one possible intervention method to reduce misinformation. However, it remains unclear under what conditions crowdsourcing fact-checking efforts deter the spread of misinformation. To address this issue, we model such distributed fact-checking as `peer policing' that will reduce the perceived payoff to share or disseminate false information (fake news) and also reward the spread of trustworthy information (real news). By simulating our model on synthetic s…

沉默胜过千言万语：虚假新闻检测中代表性不足用户的重加权技术

Silence Speaks Volumes: Re-weighting Techniques for Under-Represented Users in Fake News Detection

针对虚假新闻检测中因参与度不平等导致模型偏向活跃用户的问题，提出利用重加权技术让沉默用户发声，并研究其线索能否提升模型检测性能。

少数人的声音，多数人的观点：Twitter COVID-19假新闻分享中的社会偏见证据

The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing

本研究分析Twitter上COVID-19假新闻传播网络，发现少数创造者（约14%）主导多数错误信息，多数消费者（约86%）受其观点影响，感知多数压力或驱动信息疫情。