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User-generated content, shared with other users through social media, has increased considerably in the previous decade. In particular, the content generated by travelers, mainly online travel reviews (OTRs), has grown dramatically. This abundant recorded information has served as a basis for conducting numerous researches on big data and social media analytics. Reviewers share their OTRs on travel-related websites including peer-to-peer (P2P) accommodation platforms and online travel agencies (OTAs). The aim of this chapter is to offer an overview of the state of the art of hospitality and tourism analytics based on OTRs, and explore the possibilities of gaining insight, through OTRs, about perceived image and visitor preferences. In the context of hospitality prior to the Covid-19 pandemic, empirical substantiation is obtained by crossing paratextual data from hotels, registered on TripAdvisor and in three OTAs indexed in the Nasdaq 100 (Booking, Expedia and Ctrip), located in five tourist cities (Barcelona, Cape Town, Los Angeles, Singapore, and Sydney). Regarding the content analysis of OTRs text, although there are numerous publications on Airbnb (the main P2P lodging platform), research on the influence of Airbnb OTRs on destination image construction is scarce. Therefore, the content of the Airbnb OTRs of these five cities is explored in search of patterns and metrics that allow us to measure the image perceived and transmitted by visitors.