We propose Factual News Graph (FANG), a novel graphical social context representation
and learning framework for fake news detection. Unlike previous contextual models that …

We present a study on predicting the factuality of reporting and bias of news media. While
previous work has focused on studying the veracity of claims or documents, here we are …

Understanding attitudes expressed in texts, also known as stance detection, plays an
important role in systems for detecting false information online, be it misinformation …

Detecting offensive language on Twitter has many applications ranging from
detecting/predicting bullying to measuring polarization. In this paper, we focus on building a …

To address the dual need to examine the weaponization of social media and the nature of
non-Western propaganda, this article explores the use of Twitter bots in the Gulf crisis that …

A reasonable approach for fact checking a claim involves retrieving potentially relevant
documents from different sources (eg, news websites, social media, etc.), determining the …

We introduce a generic, language-independent method to collect a large percentage of
offensive and hate tweets regardless of their topics or genres. We harness the extralinguistic …

Given the constantly growing proliferation of false claims online in recent years, there has
been also a growing research interest in automatically distinguishing false rumors from …

Recent advancements in Large Language Models (LLMs) have significantly influenced the
landscape of language and speech research. Despite this progress, these models lack …

Abstract Recent advancements in Large Language Models (LLMs) have significantly
influenced the landscape of language and speech research. Despite this progress, these …