In this work, we propose a new platform-agnostic framework that enables accurate reconstruction of cross-platform social graphs by uncovering latent narratives, revealing that a small group of bridge users drives most narrative migration between platforms like Truth Social and X, with broad implications for content moderation and policy.
In this work, we utilize Matryoshka-based learning techniques to build hierarchical embeddings that can differentiate news articles at different levels of granularity.
Within this work, we explore the role that political ideology plays in contributing to toxicity both on an individual user level and a topic level on Twitter.
In this work, we examine the role of online misinformation in sparking political incivility and toxicity on the social media platform Reddit’s online communities or subreddits.
In this work, we perform narrative analysis on 29.0M different articles from 2022 and 2023 across 4,076 different low, mixed, and highly reliable websites.
We track the origin and spread of narratives from foreign news websites onto the Chinese social media platform Weibo.
In this work, we release a novel 54-language multilingual stance detection dataset and utilize synthetic translation and soft contrastive learning to perform multilingual stance detection.
In this work, we perform narrative analysis on 1.9M different articles across 1,334 different unreliable news websites, tracking the spread of 52,036 different stories throughout 2022.
In this work, we study the increase in machine-made/synthetic news articles across 3,074 news websites.
In this work, we study how 16 Russian media outlets have interacted with and utilized 732 Telegram channels throughout 2022.
In this work, we utilize contrastive learning with a triplet loss and synthetic data to engineer topic-aware and topic-agnostic embedding layers for performing stance detection.
In this work, we study the relationships between five prominent conspiracy theories (QAnon, COVID, UFO/Aliens, 9/11, and Flat-Earth) and the role that misinformation and political polarization play in spreading these conspiracies.
In this work, we present a quantitative analysis of the differences in coverage of the Russo-Ukrainian War amongst three different news ecosystems (Western, Chinese, Russian).
In this work, we study the coordinated information campaign to understand the most prominent disinformation narratives touted by the Russian government to English-speaking audiences.
This paper concerns QAnon’s role on the Internet and its connection to mainstream and alternative news sources.
This paper concerns counteracting information leakage in Tor relay selection algorithms.