Conference paper Open Access

Flood relevance estimation from visual and textual content in social media streams

Anastasia Moumtzidou; Stelios Andreadis; Ilias Gialampoukidis; Anastasios Karakostas; Stefanos Vrochidis; Ioannis Kompatsiaris

Disaster monitoring based on social media posts has raised a lot of interest in the domain of computer science the last decade, mainly due to the wide area of applications in public safety and security and due to the pervasiveness not solely on daily communication but also in life-threating situations. Social media can be used as a valuable source for producing early warnings of eminent disasters. This paper presents a framework to analyse social media multimodal content, in order to decide if the content is relevant to flooding. This is very important since it enhances the crisis situational awareness and supports various crisis management procedures such as preparedness. Evaluation on a benchmark dataset shows very good performance in both text and image classification modules.

Files (808.0 kB)
Name Size
smerp-2018_submit.pdf
md5:f2be148187961f2f22ebbd7e252688af
808.0 kB Download
24
42
views
downloads
Views 24
Downloads 42
Data volume 33.9 MB
Unique views 20
Unique downloads 40

Share

Cite as