Artificial intelligence to reduce misleading publications on social networks

Author:

Ubillús José Armando TiznadoORCID,Ladera-Castañeda MaryselaORCID,Pacherres César Augusto AtocheORCID,Pacherres Miguel Ángel AtocheORCID,Saavedra Carmen Lucila InfanteORCID

Abstract

In this paper we investigated about the potential problems occurring worldwide, regarding social networks with misleading advertisements where some authors applied some artificial intelligence techniques such as: Neural networks as mentioned by Guo, Z., et. al, (2021), sentiment analysis, Paschen (2020), Machine learning, Burkov (2019) cited in Kaufman (2020) and, to combat fake news in front of such publications by social networks in this study were able to identify if these techniques allow to solve the fear that people feel of being victims of misleading news or fake videos without checking concerning covid-19. In conclusion, it was possible to detail in this paper that the techniques applied with artificial intelligence used did not manage to identify misleading news in a deep way. These techniques used are not real-time applications, since each artificial intelligence technique is separately, extracting data from the information of social networks, generating diagnoses without real-time alerts.

Publisher

European Alliance for Innovation n.o.

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Software

Reference112 articles.

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