Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Apr 2019.
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Citing papers per year: 2022: 5.
5 papers.
- 2022Graph Neural Network Enhanced Language Models for Efficient Multilingual Text Classificationcited by 5
- 2022Geo-Information Harvesting from Social Media Datacited by 5
- 2022Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive Approach Using Transformerscited by 3
- 2022Cross-Lingual and Cross-Domain Crisis Classification for Low-Resource Scenarioscited by 3
- 2022Analyzing social media with crowdsourcing in Crowd4SDGcited by 0
- 2022Geo-Information Harvesting from Social Media Data1 Nov 2022
- 2022Cross-Lingual and Cross-Domain Crisis Classification for Low-Resource Scenarios5 Sep 2022
- 2022Analyzing social media with crowdsourcing in Crowd4SDG4 Aug 2022
- 2022Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive Approach Using Transformers21 Apr 2022
- 2022Graph Neural Network Enhanced Language Models for Efficient Multilingual Text Classification6 Mar 2022