CrisisMMD: Multimodal Twitter Datasets from Natural Disasters

Firoj Alam · Ferda Ofli · Muhammad Imran

389 citations0/0 files storedProceedings of the International AAAI Conference on Web and Social Media

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Public Relations and Crisis Communication Disaster Management and Resilience Energy and Environmental Systems

Abstract

During natural and man-made disasters, people use social media platforms such as Twitter to post textual and multimedia content to report updates about injured or dead people, infrastructure damage, missing or found people, among other information types. Studies have revealed that this online information, if processed timely and effectively, is extremely useful for humanitarian organizations to gain situational awareness and plan relief operations. In addition to the analysis of textual content, recent studies have shown that imagery content on social media can boost disaster response significantly. Despite extensive research that mainly focuses on textual content to extract useful information, limited work has focused on the use of imagery content or the combination of both content types. One of the reasons is the lack of labeled imagery data in this domain. Therefore, in this paper, we aim to tackle this limitation by releasing a large multi-modal dataset from natural disasters collected from Twitter. We provide three types of annotations, which are useful to address a number of crisis response and management tasks for different humanitarian organizations.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 389 citations exist upstream.

References

2010Microblogging during two natural hazards events 2014Social media and disasters: a functional framework for social media use in disaster planning, response, and research 2015Processing Social Media Messages in Mass Emergency 2015What to Expect When the Unexpected Happens 2014CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises

Cited by

2019Social media for intelligent public information and warning in disasters: An interdisciplinary review 2020Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities, Challenges, and Future Directions 2020A Hybrid Machine Learning Pipeline for Automated Mapping of Events and Locations From Social Media in Disasters 2019Natural disasters detection in social media and satellite imagery: a survey 2019Descriptive and visual summaries of disaster events using artificial intelligence techniques: case studies of Hurricanes Harvey, Irma, and Maria 2021HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks 2020Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.