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Found 11 papers, 5 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.
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
NELA-GT-2018: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
In this paper, we present a dataset of 713k articles collected between 02/2018-11/2018.
Computers and Society
Models for Predicting Community-Specific Interest in News Articles
To answer these questions, we compute well-studied content-based features on over 60K news articles from 4 communities on reddit. com.
An Exploration of Unreliable News Classification in Brazil and The U.S
Our results show that features related to the writing style were prominent in both data sets and, despite the language difference, some features have a universal behavior, being significant to both US and Brazilian news articles.
Sampling the News Producers: A Large News and Feature Data Set for the Study of the Complex Media Landscape
In this paper, we discuss the first release of the data set and demonstrate 4 use cases of the data and features: news characterization, engagement characterization, news attribution and content copying, and discovering news narratives.
Computers and Society
This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News
The problem of fake news has gained a lot of attention as it is claimed to have had a significant impact on 2016 US Presidential Elections.
