Data related to the paper "Studying social unrest through the lens of social media"

<br>Dataset corresponding to the paper "Studying social unrest through the lens of social media".<br>107,674 geolocated visual posts from a social media were collected during and after the 'Nahel Merzouk' riots in the summer 2023 in 7 French cities. These posts were fed to a computer vision model with the objective of identifying riot-related posts. This dataset contains the metadata (date, time, and location) of those posts along with the label of the posts (according to the model). Riot-related posts are then clustered into "events", based on their spatiotemporal proximity (see paper for more details).<br>Columns:"timestamp" (TIMESTAMP): Date and time of the posts"latitude" (REAL): Latitude at which the post was published"longitude" (REAL): Longitude at which the post was published"pred_class" (INTEGER): Binary variable with value 1 if it represents a riot, 0 otherwise"event" (TEXT): Event associated to the post, structured as follows:"No event" if the post is not marked as riot-related"day_city_id" with "day" being the day of the month associated to the event, such as "2", "city" being the city in which the event happened, such as "Paris", "id" being an integer. "29_Marseille_0" corresponds to event "0" happening in Marseille on June 29th 2023. If the value of the id is "-1", the post could not be associated to any event.