Interactive Narrative Analytics: Bridging Computational Narrative Extraction and Human Sensemaking

TL;DR

Interactive Narrative Analytics (INA) integrates computational methods and visual tools to help humans interpret and explore large, complex news narratives, addressing challenges like scalability and misinformation.

Contribution

This paper introduces INA as a new interdisciplinary approach combining computational narrative extraction with interactive visual analytics for improved sensemaking.

Findings

INA enables interactive exploration of narrative structures.

INA addresses scalability and interactivity challenges.

Potential applications include news analysis and social media exploration.

Abstract

Information overload and misinformation create significant challenges in extracting meaningful narratives from large news collections. This paper defines the nascent field of Interactive Narrative Analytics (INA), which combines computational narrative extraction with interactive visual analytics to support sensemaking. INA approaches enable the interactive exploration of narrative structures through computational methods and visual interfaces that facilitate human interpretation. The field faces challenges in scalability, interactivity, knowledge integration, and evaluation standardization, yet offers promising opportunities across news analysis, intelligence, scientific literature exploration, and social media analysis. Through the combination of computational and human insight, INA addresses complex challenges in narrative sensemaking.