相关论文: Meaningful Context, a Red Flag, or Both? Users' Pr…
The rise of social media has enabled the widespread propagation of fake news, text that is published with an intent to spread misinformation and sway beliefs. Rapidly detecting fake news, especially as new events arise, is important to…
Social media platforms offer flagging, a technical feature that empowers users to report inappropriate posts or bad actors to reduce online harm. The deceptively simple flagging interfaces on nearly all major social media platforms disguise…
Detecting misinformation threads is crucial to guarantee a healthy environment on social media. We address the problem using the data set created during the COVID-19 pandemic. It contains cascades of tweets discussing information weakly…
The proliferation of harmful and offensive content is a problem that many online platforms face today. One of the most common approaches for moderating offensive content online is via the identification and removal after it has been posted,…
Users polarization and confirmation bias play a key role in misinformation spreading on online social media. Our aim is to use this information to determine in advance potential targets for hoaxes and fake news. In this paper, we introduce…
In this work, we examine the influence of unreliable information on political incivility and toxicity on the social media platform Reddit. We show that comments on articles from unreliable news websites are posted more often in…
Misinformation about climate change poses a significant threat to societal well-being, prompting the urgent need for effective mitigation strategies. However, the rapid proliferation of online misinformation on social media platforms…
Given a choice between charts with minimal text and those with copious textual annotations, participants in a study (Stokes et al.) tended to prefer the charts with more text. This paper examines the qualitative responses of the…
As recent events have demonstrated, disinformation spread through social networks can have dire political, economic and social consequences. Detecting disinformation must inevitably rely on the structure of the network, on users…
Social media platforms provide a rich environment for analyzing user behavior. Recently, deep learning-based methods have been a mainstream approach for social media analysis models involving complex patterns. However, these methods are…
Political misinformation, particularly harmful when it aligns with individuals' preexisting beliefs and political ideologies, has become widespread on social media platforms. In response, platforms like Facebook and X introduced warning…
In this position paper we approach problems concerning critical digital and information literacy with ideas to provide more digestible explanations of abstract concepts through interface design. In particular, we focus on social media…
Social media misinformation harms individuals and societies and is potentialized by fast-growing multi-modal content (i.e., texts and images), which accounts for higher "credibility" than text-only news pieces. Although existing supervised…
During COVID-19, misinformation on social media affects the adoption of appropriate prevention behaviors. It is urgent to suppress the misinformation to prevent negative public health consequences. Although an array of studies has proposed…
The digital spread of misinformation is one of the leading threats to democracy, public health, and the global economy. Popular strategies for mitigating misinformation include crowdsourcing, machine learning, and media literacy programs…
The pervasive spread of misinformation and disinformation poses a significant threat to society. Professional fact-checkers play a key role in addressing this threat, but the vast scale of the problem forces them to prioritize their limited…
The online spreading of fake news is a major issue threatening entire societies. Much of this spreading is enabled by new media formats, namely social networks and online media sites. Researchers and practitioners have been trying to answer…
Bayesian Persuasion is proposed as a tool for social media platforms to combat the spread of misinformation. Since platforms can use machine learning to predict the popularity and misinformation features of to-be-shared posts, and users are…
This paper presents the research of the influence of cognitive, behavioral, representational factors on the susceptibility of the participants in social networks to misinformation, as well as on the activity of the nodes in this regard. The…
The widespread prevalence of misinformation poses significant societal concerns. Out-of-context misinformation, where authentic images are paired with false text, is particularly deceptive and easily misleads audiences. Most existing…