面向情绪分类的情绪词向量学习

doi:10.6040/j.issn.1671-9352.1.2016.072

Abstract

Abstract: We present a method for emotion classification based on word vector learning which considering the inner patterns and emotion labels of words. Based on the CBOW model, we introduce the inner patterns and the emotion label, in order to enrich the emotional semantics of the word vectors. For one input document, according to the TF-IDF weight of the word, we use the weighted linear combination as the text representation. We use the word vectors or text vectors as the input of the emotion classifier, using machine learning classification method(LR, SVM, CNN), to verify the experimental results in emotion classification task. Experiments show that the presented algorithm performs better than CBOW model.

Key words: word embedding, emotion analysis, emotion labels, emotion classification, word inner pattern

CLC Number:

TP391.1

DU Man, XU Xue-ke, DU Hui, WU Da-yong, LIU Yue, CHENG Xue-qi. Emotion-specific word embedding learning for emotion classification[J].JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(7): 52-58.

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Emotion-specific word embedding learning for emotion classification

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