A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. (February 2017) - Xiang, Zheng; Du, Qianzhou; Ma, Yufeng; Fan, Weiguo
Abstract: Online consumer reviews have been studied for various research problems in hospitality and tourism. However, existing studies using review data tend to rely on a single data source and data quality is largely anecdotal. This greatly limits the generalizability and contribution of social media analytics research. Through text analytics this study comparatively examines three major online review platforms, namely TripAdvisor, Expedia, and Yelp, in terms of information quality related to online reviews about the entire hotel population in Manhattan, New York City. The findings show that there are huge discrepancies in the representation of the hotel industry on these platforms. Particularly, online reviews vary considerably in terms of their linguistic characteristics, semantic features, sentiment, rating, usefulness as well as the relationships between these features. This study offers a basis for understanding the methodological challenges and identifies several research directions for social media analytics in hospitality and tourism. Highlights: We applied text analytics to compare three major online review platforms, namely, TripAdvisor, Expedia, and Yelp. Findings show discrepancies in the representation of hotel product on these platforms. Information quality, measured by linguistic and semantic features, sentiment, rating, and usefulness, varies considerably. This study is the first to comparatively explore data quality in social media studies in hospitality and tourism. This study highlights methodological challenges and contributes to the theoretical development of social media analytics.