Author Bios (50 Words for each Author)

Farshid Mirzaalian, B.Eng., MBA, is a PhD student in the area of hospitality and tourism marketing in the University of Alberta, Canada. Farshid’s research interests include consumer behaviour analysis, sentiment and opinion mining, text analytics, social media analytics, spatial analysis, big data and Geographic Information Systems (GIS) and business analytics in the hospitality and tourism.

Elizabeth Halpenny, PhD, teaches and conducts research in the areas of tourism, marketing, environmental psychology and protected areas management. Elizabeth’s research focuses on individual's interactions with nature environments, tourism experience, and environmental stewardship. Current research projects include: (a) the effect of mobile digital technologies on visitors’ experiences: (b) the impact of World Heritage designation and other park-related brands on travel decision making; (c) individuals’ attitudes towards and stewardship of natural areas; and (d) children, health and nature.

Abstract (150 Words)

User-generated content across social media platforms is playing an increasingly important role in the tourism context. Understanding tourists’ experiences and opinions about tourism destinations has led to numerous opportunities to provide tourism providers and decision-makers with greater insight. Identifying sentiments, detecting topics of interest, and exploring loyalty behaviors from user-generated content can provide valuable direction for managerial decisions. Few if any studies on social media analytics have demonstrated the support for strategic decision-making. This paper presents a novel and inclusive approach that uses different analytical techniques such as sentiment analysis and topic modeling to extract sentiments and topics of interest from tourists’ conversational data on TripAdvisor from 2002 to 2019, and also explore destination loyalty statements using a keyword clustering approach. Previous destination loyalty literature was used to develop a keyword list that was applied to search for expression of loyalty in online reviews. The robustness of loyalty clusters and optimal number of clusters was also assessed prior to final analysis. Four leading loyalty-focused categories of destination offerings were observed: glaciers, waterfalls, lakes and islands, and hiking and trails. Prioritization of visitor experience enhancements relating to these loyalty inducing destination components are discussed.

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Exploring Destination Loyalty: Application of Social Media Analytics in a Nature-based Tourism Setting

User-generated content across social media platforms is playing an increasingly important role in the tourism context. Understanding tourists’ experiences and opinions about tourism destinations has led to numerous opportunities to provide tourism providers and decision-makers with greater insight. Identifying sentiments, detecting topics of interest, and exploring loyalty behaviors from user-generated content can provide valuable direction for managerial decisions. Few if any studies on social media analytics have demonstrated the support for strategic decision-making. This paper presents a novel and inclusive approach that uses different analytical techniques such as sentiment analysis and topic modeling to extract sentiments and topics of interest from tourists’ conversational data on TripAdvisor from 2002 to 2019, and also explore destination loyalty statements using a keyword clustering approach. Previous destination loyalty literature was used to develop a keyword list that was applied to search for expression of loyalty in online reviews. The robustness of loyalty clusters and optimal number of clusters was also assessed prior to final analysis. Four leading loyalty-focused categories of destination offerings were observed: glaciers, waterfalls, lakes and islands, and hiking and trails. Prioritization of visitor experience enhancements relating to these loyalty inducing destination components are discussed.