FACADE: Fake Articles Classification and Decision Explanation
Authors: 
Erasmo Purificato, 
Saijal Shahania, Marcus Thiel, 
Ernesto William De LucaAuthors Info & Claims
Pages 294 - 299
Abstract
The daily use of social networks and the resulting dissemination of disinformation over those media have greatly contributed to the rise of the fake news phenomenon as a global problem. Several manual and automatic approaches are currently in place to try to tackle and defuse this issue, which is becoming nearly uncontrollable. In this paper, we propose Facade, a fake news detection system that aims to provide a complete solution for classifying news articles and explain the motivation behind every prediction. The system is designed with a cascading architecture composed of two classification pipelines dealing with either low-level or high-level descriptors, with the overall goal of achieving a consistent confidence score on each outcome. In addition, the system is equipped with an explainable user interface through which fact-checkers and content managers can visualise in detail the features leading to a certain prediction and have the possibility for manual cross-checking.
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Information
Published In
Apr 2023
634 pages
ISBN:978-3-031-28240-9
DOI:10.1007/978-3-031-28241-6
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 02 April 2023
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