Search Results for author:
Found 7 papers, 3 papers with code
NELA-GT-2022: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
In this paper, we present the fifth installment of the NELA-GT datasets, NELA-GT-2022.
The MeLa BitChute Dataset
In this paper we present a near-complete dataset of over 3M videos from 61K channels over 2. 5 years (June 2019 to December 2021) from the social video hosting platform BitChute, a commonly used alternative to YouTube.
Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks
The goal of LSC is to characterize and quantify language variations with respect to word meaning, to measure how distinct two language sources are (that is, people or language models).
Tell Me Who Your Friends Are: Using Content Sharing Behavior for News Source Veracity Detection
Moreover, we show that the addition of CSN features increases the accuracy of writing style models, boosting accuracy as much as 14\% when using Random Forests.
SChME at SemEval-2020 Task 1: A Model Ensemble for Detecting Lexical Semantic Change
Our results show evidence that the number of landmarks used for alignment has a directimpact on the predictive performance of the model.
Do All Good Actors Look The Same? Exploring News Veracity Detection Across The U.S. and The U.K
A major concern with text-based news veracity detection methods is that they may not generalize across countries and cultures.
NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
In this paper, we present an updated version of the NELA-GT-2018 dataset (N{\o}rregaard, Horne, and Adal{\i} 2019), entitled NELA-GT-2019.
Computers and Society
