Related papers: Entropy-based detection of Twitter echo chambers
As the Covid-19 outbreaks rapidly all over the world day by day and also affects the lives of million, a number of countries declared complete lock-down to check its intensity. During this lockdown period, social media plat-forms have…
Since the onset of the COVID-19 pandemic, vaccines have been an important topic in public discourse. The discussions around vaccines are polarized as some see them as an important measure to end the pandemic, and others are hesitant or find…
Social media such as Twitter is a hotspot of user-generated information. In this ongoing Covid-19 pandemic, there has been an abundance of data on social media which can be classified as informative and uninformative content. In this paper,…
We present the Bayesian Echo Chamber, a new Bayesian generative model for social interaction data. By modeling the evolution of people's language usage over time, this model discovers latent influence relationships between them. Unlike…
This study examines the structural dynamics of Truth Social, a politically aligned social media platform, during two major political events: the U.S. Supreme Court's overturning of Roe v. Wade and the FBI's search of Mar-a-Lago. Using a…
We present a highly effective unsupervised framework for detecting the stance of prolific Twitter users with respect to controversial topics. In particular, we use dimensionality reduction to project users onto a low-dimensional space,…
While social networks can provide an ideal platform for up-to-date information from individuals across the world, it has also proved to be a place where rumours fester and accidental or deliberate misinformation often emerges. In this…
Understanding the dynamics of language toxicity on social media is important for us to investigate the propagation of misinformation and the development of echo chambers for political scenarios such as U.S. presidential elections. Recent…
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…
We evaluate homophily and heterophily among ideological and demographic groups in a typical opinion formation context: online discussions of current news. We analyze user interactions across five years in the r/news community on Reddit, one…
The massive amounts of data that social media generates has facilitated the study of online human behavior on a scale unimaginable a few years ago. At the same time, the much discussed apparent randomness with which people interact online…
Personalized recommendation benefits users in accessing contents of interests effectively. Current research on recommender systems mostly focuses on matching users with proper items based on user interests. However, significant efforts are…
Neural networks often learn spurious correlations when exposed to biased training data, leading to poor performance on out-of-distribution data. A biased dataset can be divided, according to biased features, into bias-aligned samples (i.e.,…
The emergence of social media has largely eased the way people receive information and participate in public discussions. However, in countries with strict regulations on discussions in the public space, social media is no exception. To…
Twitter provides an open and rich source of data for studying human behaviour at scale and is widely used in social and network sciences. However, a major criticism of Twitter data is that demographic information is largely absent.…
Online Social Media represent a pervasive source of information able to reach a huge audience. Sadly, recent studies show how online social bots (automated, often malicious accounts, populating social networks and mimicking genuine users)…
Increasing evidence suggests that a growing amount of social media content is generated by autonomous entities known as social bots. In this work we present a framework to detect such entities on Twitter. We leverage more than a thousand…
People who share similar opinions towards controversial topics could form an echo chamber and may share similar political views toward other topics as well. The existence of such connections, which we call connected behavior, gives…
Microblogging websites like Twitter have been shown to be immensely useful for spreading information on a global scale within seconds. The detrimental effect, however, of such platforms is that misinformation and rumors are also as likely…
Vaccine hesitancy, which has recently been driven by online narratives, significantly degrades the efficacy of vaccination strategies, such as those for COVID-19. Despite broad agreement in the medical community about the safety and…