abhinav-bohra/Emotional-Analysis-Multitasking-Framework

My implementation of the research paper - All-in-One: Emotion, Sentiment and Intensity Prediction using a Multi-task Ensemble Framework

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Experimental

This framework helps businesses understand the true feelings behind customer feedback, social media posts, and surveys. It takes text-based input and provides detailed insights into emotions (like joy or anger), overall sentiment (positive/negative), and the intensity of those feelings. Marketers, customer support managers, and product teams can use this to gauge reactions to their services or products.

No commits in the last 6 months.

Use this if you need granular, nuanced understanding of emotions and sentiment from large volumes of text data, rather than just basic positive or negative classifications.

Not ideal if you only need a simple, high-level sentiment score without a detailed breakdown of specific emotions or their intensity.

customer-feedback-analysis social-listening market-research brand-reputation customer-experience
No License Stale 6m No Package No Dependents
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Adoption 6 / 25
Maturity 8 / 25
Community 13 / 25

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Jupyter Notebook

License

Last pushed

Apr 16, 2021

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