Abstract
This study pioneers a novel approach to quantifying destination loyalty by leveraging algorithmic sentiment analysis of user-generated content (UGC) from ecotourism hubs in Fiji and Vanuatu. Traditional measures of destination loyalty often rely on surveys or repeat visitation data, which can be retrospective, subjective, or difficult to collect comprehensively. By analyzing over 50,000 online reviews spanning five years, this research employs natural language processing (NLP) techniques, including lexicon-based sentiment analysis and thematic clustering, to extract nuanced traveler perceptions and expressions of loyalty. The comparative analysis reveals distinct drivers of positive sentiment and loyalty indicators across the two Pacific island nations, with Fiji's ecotourism experiences often praised for their accessibility and well-developed infrastructure, while Vanuatu garners strong loyalty through its authentic cultural encounters and pristine, rugged natural environments. Findings indicate that expressed intent to return, willingness to recommend, and depth of emotional positive language in reviews serve as robust digital proxies for destination loyalty. This methodology offers destination marketing organizations (DMOs) a scalable, data-driven tool for real-time monitoring of traveler sentiment, informing strategic marketing, product development, and sustainable tourism policies in the Asia-Pacific region.
