Saved in:
Bibliographic Details
Main Authors: Zayed, Omnia, Negi, Gaurav, Manjunath, Sampritha, Pillai, Devishree, Buitelaar, Paul
Format: Recurso digital
Language:
Published: Zenodo 2025
Online Access:https://doi.org/10.5281/zenodo.15585451
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866901697718124544
author Zayed, Omnia
Negi, Gaurav
Manjunath, Sampritha
Pillai, Devishree
Buitelaar, Paul
author_facet Zayed, Omnia
Negi, Gaurav
Manjunath, Sampritha
Pillai, Devishree
Buitelaar, Paul
contents <p>We introduce LUCE, an advanced dynamic framework with an interactive dashboard for analysing opinionated text aiming to understand people-centred communication. The framework features computational modules of text classification and extraction explicitly designed for analysing different elements of opinions, e.g., sentiment/emotion, suggestion, figurative language, hate/toxic speech, and topics. We designed the framework using a modular architecture, allowing scalability and extensibility with the aim of supporting other NLP tasks in subsequent versions. LUCE comprises trained models, python-based APIs, and a userfriendly dashboard, ensuring an intuitive user experience. LUCE has been validated in a relevant environment, and its capabilities and performance have been demonstrated through initial prototypes and pilot studies.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_15585451
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle LUCE: A Dynamic Framework and Interactive Dashboard for Opinionated Text Analysis
Zayed, Omnia
Negi, Gaurav
Manjunath, Sampritha
Pillai, Devishree
Buitelaar, Paul
<p>We introduce LUCE, an advanced dynamic framework with an interactive dashboard for analysing opinionated text aiming to understand people-centred communication. The framework features computational modules of text classification and extraction explicitly designed for analysing different elements of opinions, e.g., sentiment/emotion, suggestion, figurative language, hate/toxic speech, and topics. We designed the framework using a modular architecture, allowing scalability and extensibility with the aim of supporting other NLP tasks in subsequent versions. LUCE comprises trained models, python-based APIs, and a userfriendly dashboard, ensuring an intuitive user experience. LUCE has been validated in a relevant environment, and its capabilities and performance have been demonstrated through initial prototypes and pilot studies.</p>
title LUCE: A Dynamic Framework and Interactive Dashboard for Opinionated Text Analysis
url https://doi.org/10.5281/zenodo.15585451