suzana-ilic/NLP_affective_computing
NLP Affective Computing - text-based emotion recognition with Deep Learning and LLMs
This project helps you understand the emotions expressed in text, such as social media posts or news headlines. It takes written content as input and identifies underlying emotions like anger, joy, or sadness, or even gauges emotional intensity (valence and arousal). This is useful for researchers in computational linguistics or social science, as well as analysts looking to understand public sentiment from text.
Use this if you need to automatically identify and analyze emotions within text data, such as understanding public sentiment on social media or categorizing emotional tone in large text corpora.
Not ideal if you are looking for a simple, out-of-the-box sentiment analysis tool that only distinguishes between positive, negative, and neutral sentiments without deeper emotional granularity.
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Last pushed
Nov 10, 2025
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