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A survey on event and subevent detection from microblog data towards crisis management

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Abstract

Social media data analysis is a popular research domain since the last decade. Detecting the events and sub-events from social media posts that require special attention is one of the key research problem in this domain with wide range of applications. Particularly in the field of crisis management, event and sub-event detection can be of great benefit assisting the public safety departments to plan for quick responses. In this paper, we review the existing researches in the field of event and sub-event identification from social media based microblog data for disaster management. The contribution of the paper includes the study of research papers from two different aspects - i) Computational Steps for performing a research on event and sub-event detection from social media data, ii) Computational Techniques briefly discussing the methods adopted in recent studies pertaining to event and sub-event detection and summarization. This study would help the future researches in the social media data analytics domain for crisis management.

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Notes

  1. Footnote 2

  2. https://gar.undrr.org/report-2019

  3. https://www.unisdr.org/2016/iddr/IDDR2018_EconomicLosses.pdf

  4. https://backlinko.com/social-media-users#social-media-usage-stats

  5. https://tinyurl.com/3c3t2zzs

  6. https://aclweb.org/aclwiki/POS_Tagging_(State_of_the_art).

  7. https://www.oberlo.in/blog/twitter-statistics

  8. Event identification and analysis on Twitter https://ink.library.smu.edu.sg/etd_coll/126

  9. Disaster tweet classification using parts-of-speech tags: a domain adaptation approach http://hdl.handle.net/2097/34531

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    Shatadru Roy Chowdhury & Ujjwal Maulik

  2. Kalyani University, Kalyani, India

    Srinka Basu

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Ujjwal Maulik acknowledge the support received from DST-SERB Project (No. MTR/2019/000288) Grant at Jadavpur University.

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Chowdhury, S.R., Basu, S. & Maulik, U. A survey on event and subevent detection from microblog data towards crisis management. Int J Data Sci Anal 14, 319–349 (2022). https://doi.org/10.1007/s41060-022-00335-y

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