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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.15505537 |
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Table of Contents:
- <p>This paper presents an end-to-end sentiment analysis system designed to monitor user-generated content on<br>social media platforms like Twitter (X) and Instagram. Leveraging transformer-based models and a modular<br>Python framework, the system performs real-time sentiment classification, hashtag trend detection, and<br>engagement analytics. The processed data is visualized via dynamic dashboards using Power BI. This multiplatform pipeline helps researchers and marketers understand public opinion shifts and optimize decisionmaking strategies based on user sentiment. </p>