An exploration of the presence and flows of visitors in the city using the social media data in London

Most global cities have a large volume of visitors every day. These visitors interact with locals and have noticeable impacts on the city. London is the type of city that actively attracts and interacts with tourists. Tourists are, almost by definition, a group of “spatial users” that do not live and work within the city in the long term. The way they move and navigate through the city relates to their plans and destinations, and it is not always easy to distinguish such a group from other spatial users. Therefore, it requires a special effort to study their movement patterns and to identify the relationship between the group and space. Instead of using traditional on-site observations, this research has explored a new method for collecting and converting social media platform data into movement patterns using the data from Flickr. // Comparing with traditional data-collecting methods, the proposed method can cover a wider territory (5-km radius) and period (5 years), and most importantly, it collects users’ movement data without interfering with their regular activities, which might collect more natural movement results. The essential concept of movement data conversion is to arrange the geo-tagged photos of each Flickr user per day by the time sequence during their itinerary. The sets of sorted photos will reflect the visit order each user has gone through. The geographical data of the arranged photos can be converted into the topological travel routes. Finally, the routes will be mapped onto the base map using the proposed method. The collected data from the Flickr platform provide a wide range of information from static content to movement flow. These data are crucial in studying tourist activities and their related space.