Information Nutrition Labels: A Plugin for Online News Evaluation

Vincentius Kevin, Birte Högden, Claudia Schwenger, Ali Şahan, Neelu Madan, Piush Aggarwal, Anusha Bangaru, Farid Muradov, Ahmet Aker


Abstract
In this paper we present a browser plugin NewsScan that assists online news readers in evaluating the quality of online content they read by providing information nutrition labels for online news articles. In analogy to groceries, where nutrition labels help consumers make choices that they consider best for themselves, information nutrition labels tag online news articles with data that help readers judge the articles they engage with. This paper discusses the choice of the labels, their implementation and visualization.
Anthology ID:
W18-5505
Volume:
Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)
Month:
November
Year:
2018
Address:
Brussels, Belgium
Venues:
EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
28–33
Language:
URL:
https://aclanthology.org/W18-5505
DOI:
10.18653/v1/W18-5505
Bibkey:
Cite (ACL):
Vincentius Kevin, Birte Högden, Claudia Schwenger, Ali Şahan, Neelu Madan, Piush Aggarwal, Anusha Bangaru, Farid Muradov, and Ahmet Aker. 2018. Information Nutrition Labels: A Plugin for Online News Evaluation. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 28–33, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Information Nutrition Labels: A Plugin for Online News Evaluation (Kevin et al., 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-5505.pdf