Interactive Narrative Analytics: Bridging Computational Narrative Extraction and Human Sensemaking
It addresses narrative sensemaking challenges for fields like news analysis and intelligence, but it is incremental as it defines a nascent field without new methods or data.
This paper tackles the problem of extracting meaningful narratives from large news collections amid information overload and misinformation by defining Interactive Narrative Analytics (INA), which combines computational narrative extraction with interactive visual analytics to support sensemaking, though no concrete results or numbers are provided.
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.