Supporting and Transforming High-Stakes Investigations with Expert-Led Crowdsourcing

Expert investigators leverage their advanced skills and deep experience to solve complex investigations, but they face limits on their time and attention. In contrast, crowds of novices can be highly scalable and parallelizable, but lack expertise and may engage in vigilante behavior. In this dissertation, I introduce and evaluate the framework of expert-led crowdsourcing through three studies across two domains, journalism and law enforcement. First, through an ethnographic study of two law enforcement murder investigations, I uncover tensions in a real-world crowdsourced investigation and introduce the expert-led crowdsourcing framework. Second, I instantiate expert-led crowdsourcing in two collaboration systems: GroundTruth and CuriOSINTy. GroundTruth is focused on one specific investigative task, image geolocation. CuriOSINTy expands the flexibility and scope of expert-led crowdsourcing to handle more complex and multiple investigative tasks: identifying and debunking misinformation. Third, I introduce a framework for understanding how expert-led crowdsourced investigations work and how to better support them. Finally, I conclude with a discussion of how expert-led crowdsourcing enables experts and crowds to do more than either could alone, as well as how it can be generalized to other domains.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science and Applications

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2022

Author dc:creator

• Venkatagiri, Sukrit

Chair dc:contributor.committeechair

• Luther, Kurt

Committee members dc:contributor.committeemember

• Mitra, Tanushree
• North, Christopher L.
• Starbird, Kate
• Rho, Ha Rim

• expert-led crowdsourcing
• crowdsourcing
• experts
• investigations
• sensemaking
• human–computer interaction
• computer-supported collaborative work
• HCI
• CSCW

Statement dc:rights

• Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nc-sa/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:35757

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/112963