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Publiée le 25/02/2021
Post Doctorat position Geolocalization from tweets about natural disasters H/F

CDD / Mission - 18 mois 5 à 10 ans France - Centre-Val-de-Loire - (45) Orléans

> Le poste

SURICATE-Nat (www.suricatenat.fr) is a collaborative platform for the semi-automatic analysis of tweets written in French related to natural disasters (for instance, earthquakes or floods). This platform aims to exploit the testimonies immediately after a natural disaster in order to promote a rapid rise of information by citizen sensors. This involves extracting the main information from the tweets: type of disaster, damage, location etc. Location is a particularly important piece of information as it helps the relief agencies to deal with the disaster effectively. State of the art approaches for text geolocalization often fail to provide accurate location. On the one hand, unsupervised approaches mainly rely on gazetteers, and their results directly depend on the quality of these gazetteers. On the other hand, supervised approaches suffer from too small training datasets as few tweets are geolocalized by default and they are based on partitions of the geographical space that do not meet natural disasters management needs as regards location accuracy.

The main mission of the post-doctorate fellow would therefore be to propose new approaches to improve the accuracy and the precision of the automatic geolocalization of tweets, which is a necessary step to accurately describe the effects of natural disasters.

He/she will contribute to the scientific state of the art in several fields:
- recognition, extraction and contextualization of geographic information that can be found in tweets messages (spatial named entities and spatial relationships);
- spatial named entities resolution and text geocoding, especially by enriching the analysis of the spatial named entities contained in the tweets by a contextual consideration of other available knowledge (credibility of the Twitter user, analysis of its history, but also phenomenology of natural hazards, alert notifications, sensor data, etc.).

Secteurs
⟩ Aménagement : Sites / Sols

> Le profil recherché

PhD in computer science, computational social science, computational linguistics or geographic information science with knowledge in Natural Language Processing
With less than five years of postdoctoral experience.
You need to have academic publications in related works.

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