olha-kaminska/frnn_emotion_detection
Code for 3 papers: 1) "Fuzzy-Rough Nearest Neighbour Approaches for Emotion Detection in Tweets"; 2) "LT3 at SemEval-2022 Task 6: Fuzzy-Rough Nearest neighbor Classification for Sarcasm Detection"; 3) "Fuzzy Rough Nearest Neighbour Methods for Detecting Emotions, Hate Speech and Irony" by O. Kaminska, Ch. Cornelis and V. Hoste.
This project helps social media analysts and researchers automatically identify specific emotions within tweets. It takes raw tweet text as input and outputs classifications indicating the intensity of various emotions. Anyone studying public sentiment, brand perception, or social trends on Twitter would find this useful.
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Use this if you need to classify emotions like anger, joy, or sadness from large volumes of Twitter data with a method that accounts for the subtle, 'fuzzy' nature of human language.
Not ideal if you're analyzing text from sources other than Twitter or need a general sentiment analysis (positive/negative) rather than specific emotion detection.
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Mar 22, 2023
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