Towards Real-time Remote Social Sensing via Targeted Advertising

Masoomali Fatehkia, Muhammad Imran, Ingmar Weber*

*Corresponding author for this work

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

Abstract

Social media serves as an important communication channel for people affected by crises, creating a data source for emergency responders wanting to improve situational awareness. In particular, social listening on Twitter has been widely used for real-time analysis of crisis-related messages. This approach, however, is often hindered by the small fraction of (hyper-)localized content and by the inability to explicitly ask affected populations about aspects with the most operational value. Here, we explore a new form of social media data collected through targeted poll ads on Facebook. Using geo-targeted ads during flood events in six countries, we show that it is possible to collect thousands of poll responses within hours of launching the ad campaign, and at a cost of a few (US dollar) cents per response. We believe that this flexible, fast, and affordable data collection can serve as a valuable complement to existing approaches.

Original languageEnglish
Title of host publicationProceedings - 20th Global Information Systems for Crisis Response and Management Conference, ISCRAM 2023
PublisherInformation Systems for Crisis Response and Management, ISCRAM
Pages396-406
Number of pages11
ISBN (Electronic)9798218217495
Publication statusPublished - 2023
Event20th Global Information Systems for Crisis Response and Management Conference, ISCRAM 2023 - Omaha, United States
Duration: 28 May 202331 May 2023

Publication series

NameProceedings of the International ISCRAM Conference
Volume2023-text
ISSN (Electronic)2411-3387

Conference

Conference20th Global Information Systems for Crisis Response and Management Conference, ISCRAM 2023
Country/TerritoryUnited States
CityOmaha
Period28/05/2331/05/23

Keywords

  • Facebook advertising
  • flood mapping
  • real-time polling
  • remote social sensing

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