Document Type
Conference Proceeding
Publication Date
4-26-2024
Published In
Proceedings Of The ACM On Human-Computer Interaction
Abstract
Open Source Intelligence (OSINT) investigations, which rely entirely on publicly available data such as social media, play an increasingly important role in solving crimes and holding governments accountable. The growing volume of data and complex nature of tasks, however, means there is a pressing need to scale and speed up OSINT investigations. Expert-led crowdsourcing approaches show promise, but tend to either focus on narrow tasks or domains, or require resource-intense, long-term relationships between expert investigators and crowds. We address this gap by providing a flexible framework that enables investigators across domains to enlist crowdsourced support for discovery and verification of OSINT. We use a design-based research (DBR) approach to develop OSINT Research Studios (ORS), a sociotechnical system in which novice crowds are trained to support professional investigators with complex OSINT investigations. Through our qualitative evaluation, we found that ORS facilitates ethical and effective OSINT investigations across multiple domains. We also discuss broader implications of expert-crowd collaboration and opportunities for future work.
Conference
CSCW '24: The 27th ACM Conference On Computer-Supported Cooperative Work And Social Computing
Conference Dates
November 9-13, 2024
Conference Location
San José, Costa Rica
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
A. Mukhopadhyay, Sukrit Venkatagiri, and K. Luther.
(2024).
"OSINT Research Studios: A Flexible Crowdsourcing Framework To Scale Up Open Source Intelligence Investigations".
Proceedings Of The ACM On Human-Computer Interaction.
Volume 8,
DOI: 10.1145/3637382
https://works.swarthmore.edu/fac-comp-sci/126