Assessing destination satisfaction by social media: An innovative approach using Importance-Performance Analysis. (March 2022)

• Record Type: Journal Article
• Authors: Chen, Jinyan; Becken, Susanne; Stantic, Bela
• Is Part Of: Annals of tourism research. Volume 93(2022)
• Publication Date: 2022-03
• Subjects: Importance-Performance analysis -- Tourist satisfaction -- Social media -- Sentiment analysis -- Weibo; Tourism -- Periodicals
• DOI: 10.1016/j.annals.2022.103371
• Languages: English
• ISSNs: 0160-7383

Abstract

Abstract: This paper introduces an innovative approach for assessing visitor satisfaction at the destination level by identifying attributes of interest from social media text and indirectly measuring performance and importance values. A lexicon-based method for sentiment analysis is applied to determine performance value at the destination level, while importance is calculated using an adjusted association rule mining algorithm. The results are validated with earlier survey-based attributes relevant to visitors and Australia's case. The results demonstrate encouraging accuracy, suggesting that the proposed methodology offers opportunities to assess tourist satisfaction at destinations with larger sample sizes for a lower cost and greater data collection flexibility than traditional approaches. The methods proposed could be beneficial in a wide range of tourism contexts. Highlights: Destinations are recognized from tourists' travel itineraries. Sentiment analysis is applied to identify performance at multiple destinations. The importance of each attribute is calculated proportionally at each destination. Validated results of social media data with survey data