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Fake news classificator

Authors: Ruiz Cano, Elena;

Fake news classificator

Abstract

This research will focus on classifying false news according to the style and the content. And a web service will be implemented in order to make predictions about the content of online articles and, at the same time, to retrain the classifier with the articles that it could not predict correctly.

Esta investigación se centrará en clasificar las noticias falsas según el estilo y el contenido. Además se implementará un servicio web para realizar predicciones de artículos de contenido en linea y a la vez reentrenarse con los artículos que no ha podido predecir correctamente.

Country
Spain
Keywords

fake news, classificador binari, :Informàtica [Àrees temàtiques de la UPC], Natural language processing (Computer science), aprenentatge autònom, Machine learning, Aprenentatge automàtic, Àrees temàtiques de la UPC::Informàtica, Tractament del llenguatge natural (Informàtica), binary classifier

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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
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38
52
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