AIDR: artificial intelligence for disaster response

By Muhammad Imran, Carlos Castillo, J. Lucas, Patrick Meier, Sarah Vieweg. The Web Conference, 2014

590 citations recorded by the source corpus.

How researchers see this paper

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Processing Social Media Messages in Mass Emergency (2014, methodology): “Previous research has shown that information that contributes to situational awareness is reported via Twitter (and other social media platforms) during mass emergencies [Vieweg et al. 2010; Vieweg 2012; Imran et al. 2014a].”
CrisisMMD: Multimodal Twitter Datasets from Natural Disasters (2018, background): “The use of social media such as Twitter, Facebook, and Youtube, has been explored in numerous studies (Imran et al. 2014; Vieweg et al. 2010; Imran et al. 2015; Terpstra et al. 2012; Tsou et al. 2017) for curating, analyzing and summarizing crisis-related information in order to make some decisions…”
Dialect Diversity in Text Summarization on Twitter (2020, methodology): “The tweets were collected using AIDR open-source platform (Artiﬁcial Intelligence for Disaster Response [30]).”
Big Data in Natural Disaster Management: A Review (2018, background): “Text messages are the basic source of analysis [79].”
Digital Humanitarians (2017, methodology): “The software collects, filters and classifies large-scale crisisrelated user-generated content posted to Twitter (Imran et al. 2014; Meier 2013) in order to derive actionable data.”
Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages (2016, methodology): “We collected these messages using our AIDR (Artificial Intelligence for Disaster Response) platform (Imran et al., 2014).”