1. Andes: a new fake news detection system
Authors : Giacomo Abbattista, Vito Nicola Convertini, Vincenzo Gattulli, Lucia Sarcinella
Pages : 1-7
DOI : http://dx.doi.org/10.21172/1.154.01
Keywords : Fake news, fake news detection, weight TF- IDF, Support Vector Machine, Stochastic Descent of the Gradient Abstract :In this study we present a software, called ANDES (fAke News DEtection System) able to distinguish fake from true news. ANDES is based on the idea of using two independent models for classification, based on different perspectives: domains and news. For the validation of the news is used a matrix term-documents with function of weight TF-IDF, Support Vector Machine for the classification and the Stochastic Descent of the Gradient to form the model. In the classification with respect to the second perspective, a bayesian classifier will be used, on a set of characteristics taken from the domain. The data used in the tests, have been obtained through a new scraping system, which uses instances of the browser Google Chrome.
Citing this Journal Article :Giacomo Abbattista, Vito Nicola Convertini, Vincenzo Gattulli, Lucia Sarcinella, "Andes: a new fake news detection system", Volume 15 Issue 4 - February 2020, 1-7
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