Background: The search for valid information was one of the main challenges encountered during the COVID-19 pandemic, which resulted in the development of several online alternatives. Objectives: To describe the development of a computational solution to interact with users of different levels of digital literacy on topics related to COVID-19 and to map the correlations between user behavior and events and news that occurred throughout the pandemic. Method: CoronaAI, a chatbot based on Google's Dialogflow technology, was developed at a public university in Brazil and made available on WhatsApp. The dataset with users’ interactions with the chatbot comprises approximately 7,000 hits recorded throughout eleven months of CoronaAI usage. Results: CoronaAI was widely accessed by users in search of valuable and updated information on COVID-19, including checking the veracity of possible fake news about the spread of cases, deaths, symptoms, tests and protocols, among others. The mapping of users' behavior revealed that as the number of cases and deaths increased and as COVID-19 became closer, users showed a greater need for information applicable to self-care compared to following the statistical data. In addition, they showed that the constant updating of this technology may contribute to public health by enhancing general information on the pandemic and at the individual level by clarifying specific doubts about COVID-19. Conclusion: Our findings reinforce the potential usefulness of chatbot technology to resolve a wide spectrum of citizens' doubts about COVID-19, acting as a cost-effective tool against the parallel pandemic of misinformation and fake news.

How people interact with a chatbot against disinformation and fake news in COVID-19 in Brazil: The CoronaAI case

Barbon Junior S.
2023-01-01

Abstract

Background: The search for valid information was one of the main challenges encountered during the COVID-19 pandemic, which resulted in the development of several online alternatives. Objectives: To describe the development of a computational solution to interact with users of different levels of digital literacy on topics related to COVID-19 and to map the correlations between user behavior and events and news that occurred throughout the pandemic. Method: CoronaAI, a chatbot based on Google's Dialogflow technology, was developed at a public university in Brazil and made available on WhatsApp. The dataset with users’ interactions with the chatbot comprises approximately 7,000 hits recorded throughout eleven months of CoronaAI usage. Results: CoronaAI was widely accessed by users in search of valuable and updated information on COVID-19, including checking the veracity of possible fake news about the spread of cases, deaths, symptoms, tests and protocols, among others. The mapping of users' behavior revealed that as the number of cases and deaths increased and as COVID-19 became closer, users showed a greater need for information applicable to self-care compared to following the statistical data. In addition, they showed that the constant updating of this technology may contribute to public health by enhancing general information on the pandemic and at the individual level by clarifying specific doubts about COVID-19. Conclusion: Our findings reinforce the potential usefulness of chatbot technology to resolve a wide spectrum of citizens' doubts about COVID-19, acting as a cost-effective tool against the parallel pandemic of misinformation and fake news.
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S1386505623001521-main.pdf

Accesso chiuso

Tipologia: Documento in Versione Editoriale
Licenza: Copyright Editore
Dimensione 959 kB
Formato Adobe PDF
959 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
1-s2.0-S1386505623001521-main-Post_print.pdf

embargo fino al 23/06/2024

Tipologia: Bozza finale post-referaggio (post-print)
Licenza: Creative commons
Dimensione 1.37 MB
Formato Adobe PDF
1.37 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3055530
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 2
social impact