Rumor and clickbait detection by combining information divergence measures and deep learning techniques

Oliva, Christian; Palacio-Marín, Ignacio; Lago-Fernández, Luis F.; Arroyo, David

doi:10.1145/3538969.3543791

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Cited by 2 publications

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On the Design of a Misinformation Widget (MsW) Against Cloaked Science

Arroyo,

Degli-Esposti,

Gómez-Espés

et al. 2023

Lecture Notes in Computer Science

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Amongst all types of fabricated information travelling on open social networks (OSN), scientific misinformation, or cloaked science, is particularly dangerous. Here we present the design of the TRESCA misinformation widget (Ms.W), which is both a methodology and a toolbox for investigating disinformation operations leveraging scientific communications. Ms.W follows a man-in-the-loop approach: the methodology takes into consideration ideological and psychological biases, while the toolbox integrates open source intelligence solutions for verifying the accuracy of claims and the credibility of sources. Overall, Ms.W. is a flexible investigative tool offering a REST API for advanced users, who can create and label datasets and add new functionalities to the toolbox.

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