In recent years, mobile phones and access points to free Wi-Fi services have been enhanced, which has made it easier for travellers to share their stories, pictures, and video clips online during a trip. At the same time, online travel review (OTR) websites have grown significantly, allowing users to post their travel experiences, opinions, comments, and ratings in a structured way. Moreover, Internet search engines play a crucial role in locating and presenting OTRs before and throughout a trip. This evolution of social media and information and communication technologies has upset the classic sources of information of the projected tourist destination image (TDI), allowing electronic word-of-mouth to occupy a prominent position. Hence, the aim of this paper is to propose a method based on big data technologies for analysing and measuring the perceived (and transmitted) TDI from OTRs as presented in search engines, emphasising the cognitive, spatial, temporal, evaluative, and affective TDI dimensions. To test this approach, a massive analysis of metadata processed by search engines was performed on 387,414 TripAdvisor OTRs on ``Things to Do' in ile de France, an outstanding smart tourist destination. The results obtained are consistent and allow for the extraction of insights and business intelligence.