Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach
This work addresses flood monitoring for European authorities by providing real-time social media insights, but it is incremental as it builds on existing systems and methods.
The paper tackled the problem of enhancing flood awareness by integrating social media analysis into the European Flood Awareness System, using a multilingual approach to classify flood-related messages with minimal labeled data, resulting in a prototype system that automatically triggers data collection based on flood risk warnings.
This paper describes a prototype system that integrates social media analysis into the European Flood Awareness System (EFAS). This integration allows the collection of social media data to be automatically triggered by flood risk warnings determined by a hydro-meteorological model. Then, we adopt a multi-lingual approach to find flood-related messages by employing two state-of-the-art methodologies: language-agnostic word embeddings and language-aligned word embeddings. Both approaches can be used to bootstrap a classifier of social media messages for a new language with little or no labeled data. Finally, we describe a method for selecting relevant and representative messages and displaying them back in the interface of EFAS.