FRaN-X: FRaming and Narratives-eXplorer

Fuente: arXiv
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Main Authors: Muratov, Artur, Shaikh, Hana Fatima, Jani, Vanshikaa, Mahmoud, Tarek, Xie, Zhuohan, Orel, Daniil, Singh, Aaryamonvikram, Wang, Yuxia, Joshi, Aadi, Iqbal, Hasan, Hee, Ming Shan, Sahnan, Dhruv, Nikolaidis, Nikolaos, Silvano, Purificação, Dimitrov, Dimitar, Yangarber, Roman, Campos, Ricardo, Jorge, Alípio, Guimarães, Nuno, Sartori, Elisa, Stefanovitch, Nicolas, Martino, Giovanni Da San, Piskorski, Jakub, Nakov, Preslav
Format: Preprint
Published: 2025
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author Muratov, Artur
Shaikh, Hana Fatima
Jani, Vanshikaa
Mahmoud, Tarek
Xie, Zhuohan
Orel, Daniil
Singh, Aaryamonvikram
Wang, Yuxia
Joshi, Aadi
Iqbal, Hasan
Hee, Ming Shan
Sahnan, Dhruv
Nikolaidis, Nikolaos
Silvano, Purificação
Dimitrov, Dimitar
Yangarber, Roman
Campos, Ricardo
Jorge, Alípio
Guimarães, Nuno
Sartori, Elisa
Stefanovitch, Nicolas
Martino, Giovanni Da San
Piskorski, Jakub
Nakov, Preslav
author_facet Muratov, Artur
Shaikh, Hana Fatima
Jani, Vanshikaa
Mahmoud, Tarek
Xie, Zhuohan
Orel, Daniil
Singh, Aaryamonvikram
Wang, Yuxia
Joshi, Aadi
Iqbal, Hasan
Hee, Ming Shan
Sahnan, Dhruv
Nikolaidis, Nikolaos
Silvano, Purificação
Dimitrov, Dimitar
Yangarber, Roman
Campos, Ricardo
Jorge, Alípio
Guimarães, Nuno
Sartori, Elisa
Stefanovitch, Nicolas
Martino, Giovanni Da San
Piskorski, Jakub
Nakov, Preslav
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_06974
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle FRaN-X: FRaming and Narratives-eXplorer
Muratov, Artur
Shaikh, Hana Fatima
Jani, Vanshikaa
Mahmoud, Tarek
Xie, Zhuohan
Orel, Daniil
Singh, Aaryamonvikram
Wang, Yuxia
Joshi, Aadi
Iqbal, Hasan
Hee, Ming Shan
Sahnan, Dhruv
Nikolaidis, Nikolaos
Silvano, Purificação
Dimitrov, Dimitar
Yangarber, Roman
Campos, Ricardo
Jorge, Alípio
Guimarães, Nuno
Sartori, Elisa
Stefanovitch, Nicolas
Martino, Giovanni Da San
Piskorski, Jakub
Nakov, Preslav
Computation and Language
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.
title FRaN-X: FRaming and Narratives-eXplorer
topic Computation and Language
url https://arxiv.org/abs/2507.06974