Actionable Collaborative Common Operational Picture in Crisis Situation: A Comprehensive Architecture Powered with Social Media Data

Abstract

Previous works in social media processing during crisis management highlight a paradox: citizens are extensively sharing data from the field of the crisis, while decision-makers are looking for information about the emerging risks they need to address. Several tools already exist to help taking advantage of this new important source of data. However, few made their way to decisionmakers, mainly because they remain resource-consuming. That is why the question of a tool, able to process social media in near-real time, to deliver actionable information from the field is still pending. Based on a state of the art of the Natural Language Processing tools and systems dedicated to the use of social media data to improve the situational awareness of the decision-makers, this paper aims to describe a way to provide them with a first comprehensive system which asset is to completely address the challenge, from the collection of the data to their interpretation and understanding and finally offer situational models. In this sense, the paper focuses on the thorough detail of the business and consequent technical challenges that are raised, and a work in progress proposal to address them in a comprehensive manner.

An AI framework and a metamodel for collaborative situations: Application to crisis management contexts

“…The data gathering level has been described for instance in and Bénaben et al (2017) and Fertier, Montarnal, Barthe-Delanoë, Truptil, and Benaben (2016) with the automated interpretation of data coming from sensors and opendata like weather or traffic data. This is still a topic of interest, especially regarding the question of social media data (Coche, Montarnal, Tapia, & Benaben, 2019). The information exploitation level throughout a mediation information system has been deeply described in (Bénaben et al, 2015).…”