FRaN-X: FRaming and Narratives-eXplorer

TL;DR

FRaN-X is an interactive tool that automatically detects entity mentions and classifies their narrative roles in text, supporting multiple languages and domains, to help media analysts explore framing and narratives across articles.

Contribution

It introduces a two-stage system combining sequence labeling and fine-grained role classification for multi-language narrative role detection in text.

Findings

Supports five languages and two domains.

Provides interactive visualization and entity tracking.

Enables analysis of multiple articles simultaneously.

Abstract

We present FRaN-X, a Framing and Narratives Explorer that automatically detects entity mentions and classifies their narrative roles directly from raw text. FRaN-X comprises a two-stage system that combines sequence labeling with fine-grained role classification to reveal how entities are portrayed as protagonists, antagonists, or innocents, using a unique taxonomy of 22 fine-grained roles nested under these three main categories. The system supports five languages (Bulgarian, English, Hindi, Russian, and Portuguese) and two domains (the Russia-Ukraine Conflict and Climate Change). It provides an interactive web interface for media analysts to explore and compare framing across different sources, tackling the challenge of automatically detecting and labeling how entities are framed. Our system allows end users to focus on a single article as well as analyze up to four articles simultaneously. We provide aggregate level analysis including an intuitive graph visualization that highlights the narrative a group of articles are pushing. Our system includes a search feature for users to look up entities of interest, along with a timeline view that allows analysts to track an entity's role transitions across different contexts within the article. The FRaN-X system and the trained models are licensed under an MIT License. FRaN-X is publicly accessible at https://fran-x.streamlit.app/ and a video demonstration is available at https://youtu.be/VZVi-1B6yYk.