文章基本信息

标题：A Framework for Polarity Classification and Emotion Mining from Text
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作者：Sanjeev Dhawan ; Kulvinder Singh ; Vandana Khanchi 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：8
页码：7431-7436
出版社：IJECS
摘要：No wadays Online Socia l Networks are so popular that they are become a ma jor component of an individual’s socialinteraction. They are also emotionally-rich environments where users share their emotions, feelings, ideas and thoughts. In thispaper, a novel framework is proposed for characterizing emotional interactions in social networks. The aim is to extract theemotional content of texts in online social networks. The interest is in to determine whether the text is an expression of thewriter’s emotions or not if yes then what type of emotion likes happy, sad, angry, disgust, fear, surprise. For this purpose, textmining techniques are performed on comments/messages from a social network. The framework provides a model for datacollection, feature generation, data preprocessing and data mining steps. In general, the paper presents a new perspective fo rstudying emotions’ e xpression in online social networks. The technique adopted is unsupervised; it mainly uses the k-meansclustering algorithm and nearest neighbor algorithm. Experiments show high accuracy for the model in both determiningsubjectivity of texts and predicting emotions
关键词：Online Social Networks; emotion mining; text mining; emotions; sentiment database.