Social-EOC: Serviceability model to rank social media requests for emergency operation centers

Hemant Purohit*, Carlos Castillo, Muhammad Imran, Rahul Pandev

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

38 Citations (Scopus)

Abstract

The public expects a prompt response from emergency services to address requests for help posted on social media. However, the information overload of social media experienced by these organizations, coupled with their limited human resources, challenges them to timely identify and prioritize critical requests. This is particularly acute in crisis situations where any delay may have a severe impact on the effectiveness of the response. While social media has been extensively studied during crises, there is limited work on formally characterizing serviceable help requests and automatically prioritizing them for a timely response. In this paper, we present a formal model of serviceability called Social-EOC (Social Emergency Operations Center), which describes the elements of a serviceable message posted in social media that can be expressed as a request. We also describe a system for the discovery and ranking of highly serviceable requests, based on the proposed serviceability model. We validate the model for emergency services, by performing an evaluation based on real-world data from six crises, with ground truth provided by emergency management practitioners. Our experiments demonstrate that features based on the serviceability model improve the performance of discovering and ranking (nDCG up to 25%) service requests over different baselines. In the light of these experiments, the application of the serviceability model could reduce the cognitive load on emergency operation center personnel, in filtering and ranking public requests at scale.

Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
EditorsAndrea Tagarelli, Chandan Reddy, Ulrik Brandes
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages119-126
Number of pages8
ISBN (Electronic)9781538660515
DOIs
Publication statusPublished - 24 Oct 2018
Event10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018 - Barcelona, Spain
Duration: 28 Aug 201831 Aug 2018

Publication series

NameProceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018

Conference

Conference10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
Country/TerritorySpain
CityBarcelona
Period28/08/1831/08/18

Keywords

  • Emergency Management
  • Help Intent
  • Information Overload
  • Serviceability
  • Social Media

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