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Publicação
Finding Blue Oceans in Tourism: Using Text Mining to Identify Business Opportunities in Tourism
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| 1.55 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
The amount of data produced and available are bringing innovation to well know areas. One of them is Tourism for which the use of big data is particularly useful to offer ever more personalized options to travelers. The main type of data that influence consumers preference and decisions are online reviews made in specialized websites or social networks. That happens because consumers tend to take into consideration the opinions and reviews of other travelers before deciding on a destination or where to stay. In this study, a sentiment analysis of more than 1,300 reviews retrieved from TripAdvisor shows what the main attributes that predict positive and negative online reviews are. Naïve Bayes was used as an algorithm and given a result of 75% of accuracy on the sentiment analysis. The next step was complementing the sentiment analysis by using the results to build a Blue Ocean-inspired strategy that speaks to practitioners in the sector of tourism and hospitality. The findings indicate that the targeted factors for improvement are developing venues for events, establishing a feeling of safety for consumers, and fostering brand attachment.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research and CRM
Palavras-chave
Data science Sentiment analysis Blue ocean Text mining Tourism