Cognitive scaffolding: a chatbot in social networks to analyze fake news
Supporting Agencies
- Investigación realizada gracias al apoyo del Proyecto UNAM-PAPIIT <IA302121> con título “Creencias Epistemológicas Específicas a Internet y su relación con la discriminación de noticias falsas en redes sociales” y del Proyecto UNAM-PAPIIT < TA300123> “Andamios cognitivos: Aplicaciones contra la desinformación y las noticias falsas”.
Abstract
The phenomenon of fake news shared on social networks has gone viral quickly largerly due to the way the brain processes information, emotional factors and the structure of the news itself. The objective of this study was to design and implement a chatbot used as a cognitive scaffolding for the analysis of news in social networks. The procedure was carried out in four stages: analysis of platforms to create chatbots, information search, chatbot design and implementation. It was a mixed-concurrent study with descriptive scope and non-probabilistic convenience, sampling with 29 Mexican adult participants belonging to different regions of the country. The results show that the Chatbot functioned as a cognitive scaffolding since the analysis sequence for the news item included the analysis of one's own emotions and perceptions in addition to analyzing the structure of the news. Fake news was found to elicit negative feelings in people, including emotions. While responses with "I don't believe it" type denials were frequently found to argue that the analyzed news content does not have reliable sources or sufficient foundation to be credible. It is concluded that the Chatbot had a wide acceptance by users but it can still be improved from this first experience.
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