ReSoCIO

Two-thirds of French municipalities are now considered to be exposed to natural disasters. The risk of flooding is the most frequent, while seismic risk is among the most feared in terms of the number of potential victims. This situation is likely to increase in the coming decades, due to the combination of an increase of both the frequency and intensity of certain hazards due to climate change, with demographic dynamics that tend to concentrate populations in areas at risk, especially along the coastline. As a result, and with significant territorial heterogeneity, the authorities have to deal with the diversity of hazards to establish efficient crisis management systems able to protect people and property. This requires, first and foremost, the construction of situational awareness to better target and anticipate decision-making, and requires the multiplication of feedback channels from the field. In this context, RéSoCIO aims to propose a tooled approach to demonstrate the interest and feasibility of the automated exploitation of data from the Twitter social network in the context of crises related to fast-kinetic natural disasters, focusing on the case of flash floods and earthquakes. This objective requires overpassing many specific locks, the first of which concerns the ability, in a context of natural disaster, to provide information quickly. The lifting of this lock is all the more delicate as the major societal challenge of a more targeted and rapid response to natural disasters requires tweets to be analyzed with other types of exogenous data that are rapidly available (releases of weather forecast models, earthquake characteristics, etc.), and that the analysis process is automated to allow continuous "on-the-fly" processing. Another type of lock to be lifted is related to the acceptability of this type of contribution and its potential exploitability in real context. It stems from the uncertain nature of the adoption of innovative tools - due to difficulties in use and the cultural context that can lead to their abandonment - which can only be reduced by taking into account the organizational context. On this basis, RéSoCIO offers a cross-sectional analysis of how data from Twitter can be exploited by actors involved in the operational management of natural disasters, with the main innovative feature of coupled identification of algorithmic and organizational mechanisms. The proposed work is divided into different stages: monitoring, analysis, and then merging of tweets with other data and knowledge. In a research landscape with plethoric and often non-sustainable platforms, the great specificity as well as the differentiating point of the project is to rely on 3 existing, robust and complementary platforms, allowing a rise in abstraction from the scale of raw data ( SURICATE-Nat), that of information (RIOSUITE) and that of information useful for decision-making (WikiPREDICT). The development of these 3 platforms alone proves demonstratively the consideration, and the contribution to the state of the art: they will become the natural receptacles of the methodologies of analysis developed in the project.