CohortVA: A Visual Analytic System for Interactive Exploration of Cohorts based on Historical Data

TL;DR

CohortVA is an interactive visual analytic system that helps historians explore and identify historical cohorts by integrating expert insight with large-scale historical data through novel identification models and coordinated visualizations.

Contribution

The paper introduces CohortVA, a new visual analytic system with a unique identification model and coordinated views, enhancing historical cohort analysis beyond automatic data mining methods.

Findings

Improves cohort identification accuracy

Enhances historian engagement and insight

Facilitates hypothesis generation in historical research

Abstract

In history research, cohort analysis seeks to identify social structures and figure mobilities by studying the group-based behavior of historical figures. Prior works mainly employ automatic data mining approaches, lacking effective visual explanation. In this paper, we present CohortVA, an interactive visual analytic approach that enables historians to incorporate expertise and insight into the iterative exploration process. The kernel of CohortVA is a novel identification model that generates candidate cohorts and constructs cohort features by means of pre-built knowledge graphs constructed from large-scale history databases. We propose a set of coordinated views to illustrate identified cohorts and features coupled with historical events and figure profiles. Two case studies and interviews with historians demonstrate that CohortVA can greatly enhance the capabilities of cohort identifications, figure authentications, and hypothesis generation.