DoubleCheck: Designing Community-based Assessability for Historical Person Identification

TL;DR

DoubleCheck is a framework that enhances community-based assessment of historical photo identifications by providing provenance visualizations and quality badges, improving accuracy and user experience on CWPS.

Contribution

The paper introduces DoubleCheck, a novel system architecture and interface design that supports community assessment of historical photo IDs with provenance visualization and quality indicators.

Findings

Users contributed diverse sources for photo IDs.

Provenance visualizations facilitated community assessment.

Quality badges supported accurate ID evaluations.

Abstract

Historical photos are valuable for their cultural and economic significance, but can be difficult to identify accurately due to various challenges such as low-quality images, lack of corroborating evidence, and limited research resources. Misidentified photos can have significant negative consequences, including lost economic value, incorrect historical records, and the spread of misinformation that can lead to perpetuating conspiracy theories. To accurately assess the credibility of a photo identification (ID), it may be necessary to conduct investigative research, use domain knowledge, and consult experts. In this paper, we introduce DoubleCheck, a quality assessment framework for verifying historical photo IDs on Civil War Photo Sleuth (CWPS), a popular online platform for identifying American Civil War-era photos using facial recognition and crowdsourcing. DoubleCheck focuses on improving CWPS's user experience and system architecture to display information useful for assessing the quality of historical photo IDs on CWPS. In a mixed-methods evaluation of DoubleCheck, we found that users contributed a wide diversity of sources for photo IDs, which helped facilitate the community's assessment of these IDs through DoubleCheck's provenance visualizations. Further, DoubleCheck's quality assessment badges and visualizations supported users in making accurate assessments of photo IDs, even in cases involving ID conflicts.