EmoIntens Tracker at SemEval-2018 Task 1: Emotional Intensity Levels in \#Tweets
The „Affect in Tweets{''} task is centered on emotions categorization and evaluation matrix using multi-language tweets (English and Spanish). In this research, SemEval Affect dataset was preprocessed, categorized, and evaluated accordingly (precision, recall, and accuracy). The system described in this paper is based on the implementation of supervised machine learning (Naive Bayes, KNN and SVM), deep learning (NN Tensor Flow model), and decision trees algorithms.
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BIG-bench Machine LearningEmotion RecognitionSentiment AnalysisSimilar Papers 제목 키워드 기반
DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction
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