Defining an Integrated and Computed Methodology Approach for Sentiment and Psychographic Analysis in Tourism Research

Reference: Izzo, F., Picone, Q. (2022). Defining an Integrated and Computed Methodology Approach for Sentiment and Psychographic Analysis in Tourism Research. Journal of Tourism and Services, 25(13), 1-21. doi: 10.29036/jots.v13i25.393

Authors

DOI:

https://doi.org/10.29036/jots.v13i25.393

Keywords:

Big Five Factor model, Sentiment Analysis, Machine Learning

Abstract

High-performance computational resources and artificial intelligence-based tools can enhance tourism research and marketing. However, a formal methodological approach using digital technologies in this field is still missing. This research work presents the preliminary results of defining an integrated computational methodology in tourism research and marketing. In addition, the paper aims to provide guidelines for a methodological approach leveraging technological resources and Big Data. The proposed research method is based on online User-Generated Content (UGC) analysis through a psychographic approach based on the Big Five Model, Sentiment Analysis, and Machine Learning techniques. The study is supported by high-performance computing resources, artificial intelligence-based tools, and open-source Python-based software for data collection, text analysis, and psychographic attribution. Results show a remarkable performance of the BFF prediction model and confirm the role of personality in the tourists’ decision-making and appreciation of a site. Future developments of this project involve using the acquired structured dataset labeled with sentiment and psychographic attribution to create a further prediction model on tourist segments and appreciation as part of a marketing strategy in tourism management. Future research should push forward the development of further integrated and performing computer-based methodology in tourism research and marketing, leveraging the massive amount of data and the potential of high-performance computing techniques. The main contribution of this research effort is twofold: the definition of a general-purpose BFF/Sentiment Analysis methodology and the development of a prediction model from online UGC based on the Big Five personality traits in the tourism research scenario.

Author Biographies

Federica Izzo, Department of Education, psychology and communication, University "Suor Orsola Benincasa", Naples, Italy

Affiliation: Department of Education, psychology and communication, University "Suor Orsola Benincasa", Naples, Italy.

https://www.unisob.na.it/universita/facolta/formazione/index.htm?vr=1&lg=en

Email: federica.izzo@studenti.unisob.na.it

Mrs. Izzo is a Ph.D. scholar in the "Humanities and Technologies: an integrated research path" program at University "Suor Orsola Benincasa", Naples, Italy. She is a Subject Expert and Teaching Assistant in Web Marketing. Her research reflects marketing, communication, consumer behavior, business and management studies, data analysis, machine learning, and new technologies applied to qualitative research.

Quirino Picone, University "Suor Orsola Benincasa", Naples, Italy

Affiliation: Affiliation: Department of Education, psychology and communication, University "Suor Orsola Benincasa", Naples, Italy.

https://www.unisob.na.it/universita/facolta/formazione/index.htm?vr=1&lg=en

Email: quirino.picone@docenti.unisob.na.it

Dr. Picone has a Ph.D. in "Humanities and Technologies: an integrated research path". He is an adjunct professor in Web Marketing, Web 2.0, Internet and New Media. He is also the academic coordinator of Master's courses on multimedia communication in the food and wine sector and e-commerce management. He manages all social media, communication, and web marketing activities for the University "Suor Orsola Benincasa". He is a speaker at Italian and international conferences on marketing and management.

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Published

2022-12-20