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FUSED: Fusing Social Media Stream Classification Techniques for Effective Disaster Response | IEEE Conference Publication | IEEE Xplore

FUSED: Fusing Social Media Stream Classification Techniques for Effective Disaster Response


Abstract:

Timely delivery of the right information to the right first responders can help improve the outcomes of their efforts and save lives. With social media communications (Tw...Show More

Abstract:

Timely delivery of the right information to the right first responders can help improve the outcomes of their efforts and save lives. With social media communications (Twitter, Facebook, etc.) being increasingly used to send and get information during disasters, forwarding them to the right first responders in a timely manner can be very helpful. We use Natural Language Processing and Machine Learning, to steer the social media posts to the most appropriate first responder.An important goal is to retrieve and deliver only the critical, actionable information to first responders in real-time. We examine the overall pipeline starting from retrieving tweets from the social media platforms, to their classification, and dissemination to first responders.We propose improvements in the area of data retrieval, relevance prediction and prioritizing information sent to the first responders by fusing NLP and ML classification techniques thus improving emergency response. We demonstrate the effectiveness of our proposed approach in retrieving and extracting 37,295 actionable tweets related to the IDA hurricane that occurred in the US in Aug.–Sep, 2021.
Date of Conference: 03-06 May 2022
Date Added to IEEE Xplore: 28 June 2022
ISBN Information:
Conference Location: Milan, Italy

Funding Agency:


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