Automated fact-checking for assisting human fact-checkers

Nakov, Preslav; Corney, David; Hasanain, Maram; Alam, Firoj; Elsayed, Tamer; Barron-Cede, Alberto; Papotti, Paolo; Shaar, Shaden; Da San Martino, Giovanni
IJCAI 2021, 30th International Joint Conference on Artificial Intelligence, 21-26 August, 2021, Montreal, Canada (Virtual Conference)

The reporting and analysis of current events around the globe has expanded from professional, editorlead journalism all the way to citizen journalism. Politicians and other key players enjoy direct access to their audiences through social media, bypassing the filters of official cables or traditional media. However, the multiple advantages of free speech and direct communication are dimmed by the misuse of the media to spread inaccurate or misleading claims. These phenomena have led to the modern incarnation of the fact-checker — a professional whose main aim is to examine claims using available evidence to assess their veracity. As in other text forensics tasks, the amount of information available makes the work of the fact-checker more difficult. With this in mind, starting from the perspective of the professional fact-checker, we survey the available intelligent technologies that can support the human expert in the different steps of her fact-checking endeavor. These include identifying claims worth fact-checking; detecting relevant previously fact-checked claims; retrieving relevant evidence to fact-check a claim; and actually verifying a claim. In each case, we pay attention to the challenges in future work and the potential impact on real-world fact-checking.


Type:
Conférence
City:
Montreal
Date:
2021-08-20
Department:
Data Science
Eurecom Ref:
6494
Copyright:
IJCAI
See also:

PERMALINK : https://www.eurecom.fr/publication/6494