Machine learning and sentiment analysis to assess the evolution of the COVID-19 pandemic and the impacts on tourism

Paulo Sergio Gonçalves de Oliveira; Elizabeth Kyoko Wada; Anderson Soares Lopes; Luciano Ferreira da Silva

doi:10.5281/zenodo.10325571

Authors

Paulo Sergio Gonçalves de Oliveira Professor and Full time researcher at Universidade Anhembi Morumbi, professor in graduation in Hospitatity (Master and Doctorate) as in bachelor of Computer Science and Industrial Engineering. https://orcid.org/0000-0001-9122-4904
Elizabeth Kyoko Wada Coordinator, Professor and Full time researcher at Universidade Anhembi Morumbi, professor in gradution in Hospitatity (Master and Doctorate) as in bachelor of Tourism, Events and Hospitality. https://orcid.org/0000-0001-7016-7365
Anderson Soares Lopes Phd Student of Hospitality/Universidade Anhembi Morumbi, Member of the research groups Hospitality in Service Competitiveness (Universidade Anhembi Morumbi) and CIDSGAM - City, Sustainability and Environmental Management (EACH/USP). https://orcid.org/0000-0001-9728-3841
Luciano Ferreira da Silva Professor and Full Time Researcher at Universidade Nove de Julho, Professor in post-graduation in Project Management (Professional Master and Professional Doctorate). https://orcid.org/0000-0001-6482-8729

DOI:

https://doi.org/10.5281/zenodo.10325571

Keywords:

Artificial Intelligence, Hospitality in Tourism, Sentiment Analysis, Hostility in Tourism

Abstract

This article aims to analyze how the emotional, mental, and sentimental demands related with hospitality and hostility were developed during the pandemic of the COVID-19 in Brazil. As methological procedures was applied sequential mixed methods research. Firstly, about 1,000 pieces of news were collected from two Brazilian websites to be able to manually classify them in the feelings of hospitality and hostility. We use a machine learning supervisor analysis following a sentiment analysis technique. Secondly, the data were used for training in eight machine learning algorithms, through supervised analysis, being chosen the logistic regression for the data classification, because it fits better to the data, reaching 72% of accuracy. The data collected in two years of the pandemic, thus approximately 221,000 news were then classified using the chosen algorithm, which allowed the generation of graphics and analysis through inferential statistics, through the evolution of feelings of hospitality and hostility. The results indicate that in situations such as the COVID-19 pandemic, people tend to behave hostilely, which leads to a lack of hospitality. The implications of this study are related to the ability to materialize, through the concepts of hospitality and hostility, the perception of visitors, guests, among other people, involved in the tourism sector. Therefore, the sentiment analysis from social media and news affected the tourism and hospitality industry.

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Author Biographies

Paulo Sergio Gonçalves de Oliveira, Professor and Full time researcher at Universidade Anhembi Morumbi, professor in graduation in Hospitatity (Master and Doctorate) as in bachelor of Computer Science and Industrial Engineering.

Phd of Industrial Engineerign/UNIMEP (2012). Master in Administration /USCS (2008). Degree in Administration/FIAP (2004). Professor and Full time researcher at Universidade Anhembi Morumbi, professor in graduation in Hospitatity (Master and Doctorate) as in bachelor of Computer Science and Industrial Engineering. CV: http://lattes.cnpq.br/5787786955978812 [ psoliveira@anhembi.br ]

Elizabeth Kyoko Wada, Coordinator, Professor and Full time researcher at Universidade Anhembi Morumbi, professor in gradution in Hospitatity (Master and Doctorate) as in bachelor of Tourism, Events and Hospitality.

Phd of Communications Sciences/ECA USP (1994). Master in Communications Sciences (1988). Public Relations/ECA USP (1980). Coordinator, Professor and Full time researcher at Universidade Anhembi Morumbi, professor in gradution in Hospitatity (Master and Doctorate) as in bachelor of Tourism, Events and Hospitality. CV: http://lattes.cnpq.br/4904816535433696 [ elwada@anhembi.br ]

Anderson Soares Lopes, Phd Student of Hospitality/Universidade Anhembi Morumbi, Member of the research groups Hospitality in Service Competitiveness (Universidade Anhembi Morumbi) and CIDSGAM - City, Sustainability and Environmental Management (EACH/USP).

Phd Student of Hospitality/Universidade Anhembi Morumbi, Member of the research groups Hospitality in Service Competitiveness (Universidade Anhembi Morumbi) and CIDSGAM - City, Sustainability and Environmental Management (EACH/USP). http://lattes.cnpq.br/3300579366589040 [ aslturjp@yahoo.com.br ]

Luciano Ferreira da Silva, Professor and Full Time Researcher at Universidade Nove de Julho, Professor in post-graduation in Project Management (Professional Master and Professional Doctorate).

Phd of Administration/PUC-SP (2017). Master in Education, Communication and Administration/UNIMARCO (2007). Degree of Administration/FBRH (1995). Professor and Full Time Researcher at Universidade Nove de Julho, Professor in post-graduation in Project Management (Professional Master and Professional Doctorate). CV: http://lattes.cnpq.br/3790925273077368 [ lf_silvabr@yahoo.com.br ]

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