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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15585451 |
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| _version_ | 1866901697718124544 |
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| 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 |