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An ability to infer the political leaning of social media users can help in gathering opinion polls thereby leading to a better understanding of public opinion. While there has been a body of research attempting to infer the political…

Media bias can significantly impact the formation and development of opinions and sentiments in a population. It is thus important to study the emergence and development of partisan media and political polarization. However, it is…

With the rise in popularity of public social media and micro-blogging services, most notably Twitter, the people have found a venue to hear and be heard by their peers without an intermediary. As a consequence, and aided by the public…

From a liberal perspective, pluralism and viewpoint diversity are seen as a necessary condition for a well-functioning democracy. Recently, there have been claims that viewpoint diversity is diminishing in online social networks, putting…

Social media platforms often foster environments where users primarily engage with content that aligns with their existing beliefs, thereby reinforcing their views and limiting exposure to opposing viewpoints. In this paper, we analyze X…

We propose a fully unsupervised method to detect bias in contextualized embeddings. The method leverages the assortative information latently encoded by social networks and combines orthogonality regularization, structured sparsity…

Social media play a significant role in shaping public opinion and influencing ideological communities through information propagation. Our demo InfoPattern centers on the interplay between language and human ideology. The demo (Code:…

Polarized topics often spark discussion and debate on social media. Recent studies have shown that polarized debates have a specific clustered structure in the endorsement net- work, which indicates that users direct their endorsements…

Social media has brought a revolution on how people are consuming news. Beyond the undoubtedly large number of advantages brought by social-media platforms, a point of criticism has been the creation of echo chambers and filter bubbles,…

Social media platforms are rife with politically charged discussions. Therefore, accurately deciphering and predicting partisan biases using Large Language Models (LLMs) is increasingly critical. In this study, we address the challenge of…

The proliferation of online social networks has significantly reshaped the way individuals access and engage with information. While these platforms offer unprecedented connectivity, they may foster environments where users are increasingly…

In the age of information abundance, attention is a coveted resource. Social media platforms vigorously compete for users' engagement, influencing the evolution of their opinions on a variety of topics. With recommendation algorithms often…

Quantification of the political leaning of online news articles can aid in understanding the dynamics of political ideology in social groups and measures to mitigating them. However, predicting the accurate political leaning of a news…

Developing machine learning models to characterize political polarization on online social media presents significant challenges. These challenges mainly stem from various factors such as the lack of annotated data, presence of noise in…

Even though the Internet and social media have increased the amount of news and information people can consume, most users are only exposed to content that reinforces their positions and isolates them from other ideological communities.…

Twitter, a microblogging service, has evolved into a powerful communication platform with millions of active users who generate immense volume of microposts on a daily basis. To facilitate effective categorization and easy search, users…

Social network websites, such as Facebook, YouTube, Lastfm etc, have become a popular platform for users to connect with each other and share content or opinions. They provide rich information for us to study the influence of user's social…

Social media users express their political preferences via interaction with other users, by spontaneous declarations or by participation in communities within the network. This makes a social network such as Twitter a valuable data source…

In recent years, there has been significant interest in understanding users' online content consumption patterns. But, the unstructured, high-dimensional, and dynamic nature of such data makes extracting valuable insights challenging. Here…

The analysis of social networks enables the understanding of social interactions, polarisation of ideas, and the spread of information and therefore plays an important role in society. We use Twitter data - as it is a popular venue for the…