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Social media platforms have facilitated the rapid spread of dis- and mis-information. Parler, a US-based fringe social media platform that positions itself as a champion of free-speech, has had substantial information integrity issues. In…
Social media streams contain large and diverse amount of information, ranging from daily-life stories to the latest global and local events and news. Twitter, especially, allows a fast spread of events happening real time, and enables…
The COVID-19 pandemic introduced new norms such as social distancing, face masks, quarantine, lockdowns, travel restrictions, work/study from home, and business closures, to name a few. The pandemic's seriousness made people vocal on social…
The recent global outbreak of the coronavirus disease (COVID-19) has spread to all corners of the globe. The international travel ban, panic buying, and the need for self-quarantine are among the many other social challenges brought about…
Disinformation has become a serious problem on social media. In particular, given their short format, visual attraction, and humorous nature, memes have a significant advantage in dissemination among online communities, making them an…
The discourse around conspiracy theories is currently thriving amidst the rampant misinformation in online environments. Research in this field has been focused on detecting conspiracy theories on social media, often relying on limited…
During broadcast events such as the Superbowl, the U.S. Presidential and Primary debates, etc., Twitter has become the de facto platform for crowds to share perspectives and commentaries about them. Given an event and an associated…
Detecting harmful content on social media, such as Twitter, is made difficult by the fact that the seemingly simple yes/no classification conceals a significant amount of complexity. Unfortunately, while several datasets have been collected…
The detection of events from online social networks is a recent, evolving field that attracts researchers from across a spectrum of disciplines and domains. Here we report a time-series analysis for predicting events. In particular, we…
With the increase in popularity of deep learning models for natural language processing (NLP) tasks, in the field of Pharmacovigilance, more specifically for the identification of Adverse Drug Reactions (ADRs), there is an inherent need for…
We describe Mega-COV, a billion-scale dataset from Twitter for studying COVID-19. The dataset is diverse (covers 268 countries), longitudinal (goes as back as 2007), multilingual (comes in 100+ languages), and has a significant number of…
The conflict between Israel and Palestinians significantly escalated after the October 7, 2023 Hamas attack, capturing global attention. To understand the public discourse on this conflict, we present a meticulously compiled…
In current study, a mechanism to extract traffic related information such as congestion and incidents from textual data from the internet is proposed. The current source of data is Twitter. As the data being considered is extremely large in…
The #MeToo movement has catalyzed widespread public discourse surrounding sexual harassment and assault, empowering survivors to share their stories and holding perpetrators accountable. While the movement has had a substantial and largely…
In this paper, we present a dataset of 713k articles collected between 02/2018-11/2018. These articles are collected directly from 194 news and media outlets including mainstream, hyper-partisan, and conspiracy sources. We incorporate…
Online news and information sources are convenient and accessible ways to learn about current issues. For instance, more than 300 million people engage with posts on Twitter globally, which provides the possibility to disseminate misleading…
In recent years, social media has been criticized for yielding polarization. Identifying emerging disagreements and growing polarization is important for journalists to create alerts and provide more balanced coverage. While recent studies…
In this paper, we introduce the first release of a large-scale dataset capturing discourse on $\mathbb{X}$ (a.k.a., Twitter) related to the upcoming 2024 U.S. Presidential Election. Our dataset comprises 22 million publicly available posts…
As the COVID-19 pandemic continues its march around the world, an unprecedented amount of open data is being generated for genetics and epidemiological research. The unparalleled rate at which many research groups around the world are…
Recently, there had been little notable activity from the once prominent hacktivist group, Anonymous. The group, responsible for activist-based cyber attacks on major businesses and governments, appeared to have fragmented after key members…