Sentiment Analysis and Multimodal Approach Applied to Social Media Content in Hospitality Industry

Abstract

Purpose – The importance of the "data gold rush" that occurs in real time on various social media platforms is recognized by various tourism stakeholders and researcher. To extract knowledge from textual data, the purpose of this study is to apply text mining techniques to social media data. Methodology – Descriptive statistical analysis is conducted to quantify the activity of hotel brands on Facebook. The topic modelling technique Latent Dirichlet Allocation (LDA) is used to extract and validate knowledge from text data of 25 Croatian four- and five- star hotel brands that were active on social media in 2019. Sentiment analysis is used to identify personal attitudes expressed through user-generated text that hotel brands promote by posting messages on Facebook pages. Findings – The LDA analysis of the Croatian hotel posts extracted 6 topics: Wellbeing, Atmosphere, Promotion, Gastronomy, Surrounding and Satisfaction. The results of the sentiment analysis indicated that Facebook page followers are more likely to express positive sentiments reflecting an overall satisfaction with the promoted products, services and staff by hotel brands. Contribution – It is a unique study that provides an analysis of textual data in Croatian hospitality research. The application of the multimodal approach contributes to a better uses of contents in possible different strategies so that effective indicators can be given to perform an effective communication. This study provides recommendations, challenges, and current insights into applied communication strategies for marketers to increase a greater number of tourists visiting destinations.

Development Of Sentiment Analysis Model In Kazakh Language To Analyze Reviews

“…Studies [8][9][10] analyze cultural aspects and sentiment in the hospitality and service industry using data from reviews on TripAdvisor and social media analysis. The study [8] analyzed 390,236 terms from complaints from guests from 63 countries staying in 353 hotels in the UK to identify cultural differences in service perceptions between Asian and non-Asian customers.…”

“…The study [8] analyzed 390,236 terms from complaints from guests from 63 countries staying in 353 hotels in the UK to identify cultural differences in service perceptions between Asian and non-Asian customers. In [9], a multimodal analysis of social media content in the hospitality industry was carried out, emphasizing the low engagement between hotel brands and users. The work of [10] reveals the importance of Hispanic employees in the hospitality industry, emphasizing the need to address their needs to improve overall satisfaction and performance.…”

Nfts: What Opportunities and Challenges in Tourism?

“…The evaluation method underlying customer satisfaction metrics consists of short questionnaires that allow qualitative and quantitative assessments, also supporting subsequent evaluations of the economic impact of any critical issues (in a negative sense) and proposals for improvement (in a positive sense). The most useful and easyto-implement metrics and related KPIs are the Net Promoter Score (NPS), Sentiment Analysis (Musanovic, Folgieri, Gregoric, 2021;Folgieri, Baldigara, Gricar, 2020;Folgieri, Bait, Carrion, 2016), and Rating and Ranking variations.…”

“…In previous works (Musanovic, Folgieri, Gregoric, 2021;Folgieri, Baldigara, Gricar, 2020;Folgieri, Bait, Carrion, 2016) we discussed the contribution of digital platforms as a means to improve the reputation of a country (i.e. Sentiment Analysis), analysing the possible opportunities given by virtual tourism (Folgieri and Bait, 2014).…”