omarsar/emotion_analysis_elastic_pytorch
Deep Emotion Analysis with Elastic and PyTorch
This project helps researchers and data scientists analyze emotions from social media data in real-time. It takes raw text data, like tweets, processes it to identify emotions, and then organizes this information for easy search and visualization. The output is a structured dataset that can be explored to answer research questions about public sentiment and emotional trends.
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Use this if you need to perform real-time emotion analysis on text data, especially from social media, and want to integrate deep learning insights with powerful search and visualization tools.
Not ideal if you need a plug-and-play solution without any setup, as it involves integrating multiple components like Elasticsearch and PyTorch.
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Last pushed
Nov 12, 2018
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