Hospitality and tourism industries have recognized that engaging with customers via social media is now a critical element of their marketing strategy. Given the high variability of success with which firms have been attracting customer interest online, businesses are clearly struggling to determine exactly the right methods to use the newest technologies. This study presents a predictive model of attributes for online posts that evoke a high level of customer engagement. The contribution to the literature is a unique set of features that have significant impact on customer engagement, using a big-data set to support findings. In accordance with theories originating from Social Belongingness and Brand Community Marketing, findings indicate that appeals to a sense of community belonging have a significant impact on customer engagement in social media. Specifically, communities have idiomatic vocabularies consisting of “activation words” that are especially effective for engaging customers on social media. This has both theoretical implications in that it constitutes a large-scale, real-world confirmation of belongingness hypotheses, and managerial implications in that it suggests best practices for maintaining an online presence.

• Richard Gruss(Radford University, USA)
• Eojina Kim(Virginia Tech, USA)
• Alan Abrahams(Virginia Tech, USA)
• Yuuyun Song(Virginia Tech, USA)
• Daniel Berry(Virginia Tech, USA)