相关论文: Analyzing the temporal dynamics of linguistic feat…
There is a widespread belief that the tone of US political language has become more negative recently, in particular when Donald Trump entered politics. At the same time, there is disagreement as to whether Trump changed or merely continued…
The use of abusive language online has become an increasingly pervasive problem that damages both individuals and society, with effects ranging from psychological harm right through to escalation to real-life violence and even death.…
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…
Following recent policy changes by X (Twitter) and other social media platforms, user interaction data has become increasingly difficult to access. These restrictions are impeding robust research pertaining to social and political phenomena…
Social media platforms enhance the propagation of online misinformation by providing large user bases with a quick means to share content. One way to disrupt the rapid dissemination of misinformation at scale is through warning tags, which…
The extensive dissemination of false information in social networks affects netizens social lives, morals, and behaviours. When a neighbour expresses strong emotions (e.g., fear, anger, excitement) based on a false statement, these emotions…
Background: Studies examining how sentiment on social media varies depending on timing and location appear to produce inconsistent results, making it hard to design systems that use sentiment to detect localized events for public health…
Misinformation poses a growing global threat to institutional trust, democratic stability, and public decision-making. While prior research has often portrayed social media as a channel for spreading falsehoods, less is known about the…
Both politics and pandemics have recently provided ample motivation for the development of machine learning-enabled disinformation (a.k.a. fake news) detection algorithms. Existing literature has focused primarily on the fully-automated…
The spread of election misinformation and harmful political content conveys misleading narratives and poses a serious threat to democratic integrity. Detecting harmful content at early stages is essential for understanding and potentially…
Social media has become extremely influential when it comes to policy making in modern societies, especially in the western world, where platforms such as Twitter allow users to follow politicians, thus making citizens more involved in…
The massive diffusion of online social media allows for the rapid and uncontrolled spreading of conspiracy theories, hoaxes, unsubstantiated claims, and false news. Such an impressive amount of misinformation can influence policy…
The rise of misinformation and fake news in online political discourse poses significant challenges to democratic processes and public engagement. While debunking efforts aim to counteract misinformation and foster fact-based dialogue,…
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…
Since the information available is fundamental for our perceptions and opinions, we are interested in understanding the conditions allowing for a good information to be disseminated. This paper explores opinion dynamics by means of…
Large Language Models (LLMs) have demonstrated impressive capabilities in reasoning, positioning them as promising tools for supporting human problem-solving. However, what happens when their performance is affected by misinformation, i.e.,…
Opinion Dynamics is an interdisciplinary area of research. Psychology and Sociology have proposed models of how individuals form opinions and how social interactions influence this process. Socio-Physicists have interpreted patterns in…
The Covid-19 pandemic has sparked renewed attention on the prevalence of misinformation online, whether intentional or not, underscoring the potential risks posed to individuals' quality of life associated with the dissemination of…
When users on social media share content without considering its veracity, they may unwittingly be spreading misinformation. In this work, we investigate the design of lightweight interventions that nudge users to assess the accuracy of…
Statistical methods applied to social media posts shed light on the dynamics of online dialogue. For example, users' wording choices predict their persuasiveness and users adopt the language patterns of other dialogue participants. In this…