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Recent disasters have demonstrated that an immense amount of information is shared using social networks before, during and after large-scale disaster events (Twitter, 2012). Accessing such information in real-time and in a methodological manner would allow disaster responders to allocate resources more efficiently. This paper presents an initial research framework related to aggregating, assessing, and diffusing information relevant to a disaster. A hybrid approach, utilizing automated data mining tools and crowdsourcing to optimize the information evaluation process, is suggested. Furthermore, a research framework for future disaster informatics research is presented. This paper informs information systems researchers, disaster planning organizations, government entities and organizations interested in utilizing real-time information to make sound decisions. Specifically, recent research of social networks presents a unique opportunity to evaluate information systems that must make sense of large quantities of data in a short period of time.
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Stored only when both papers are in the corpus — 8 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.