Thursday, 23 May 2019

Video Abstract: Big data and quality data for fake news and misinformation detection

Fatemeh Torabi Asr and Maite Taboada
Big Data & Society 6(1), First published May 23, 2019.

Fake news is a problem. It is a big data problem. We are trying to solve it with small amounts of data. Those are, in a nutshell, the three main points of our paper. We review available datasets and introduce the MisInfoText repository as a contribution of our lab to the community. We make available the full text of the news articles, together with veracity labels previously assigned based on manual assessment of the articles’ truth content by fact-checkers. We also perform a topic modeling experiment to elaborate on the gaps and sources of imbalance in currently available datasets to guide future efforts. We appeal to the community to collect more data and to make it available for research purposes.

Video Abstract

This video was taken during Innovations in Research, an event at Simon Fraser University in Vancouver, as part of the Community Summit “Confronting the Disinformation Age”.

Credit: Simon Fraser University.

Keywords: Fake news, misinformation, labelled datasets, text classification, machine learning, topic modelling