Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention ...Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification.展开更多
基金This work has partially been sponsored by the Hungarian National Scientific Fund under contract OTKA 129374the Research&Development Operational Program for the project“Modernization and Improvement of Technical Infrastructure for Research and Development of J.Selye University in the Fields of Nanotechnology and Intelligent Space”,ITMS 26210120042,co-funded by the European Regional Development Fund.
文摘Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification.
