TY - GEN
T1 - Sentiment classification in turn-level interactive Chinese texts of e-learning applications
AU - Tian, Feng
AU - Liang, Huijun
AU - Li, Longzhuang
AU - Zheng, Qinghua
PY - 2012
Y1 - 2012
N2 - To solve the problem of emotional illiteracy in current e-Learning environment, researches on sentiment analysis now get more attentions. This paper focuses on recognizing emotion from interactive Chinese texts (ICTs). Through observation, firstly, characteristics of ICTs are discussed. Then two kinds of feature sets, frequency based feature set and interaction related feature set, are presented. Finally, the corresponding feature extraction and selection for ICTs are presented. To validate the feature sets and choose the best method of sentiment analysis, we carry out a number of experiments. The experiments' results show that, combining with syntax based feature set, frequency based feature set and interaction related feature set can improve algorithm classification performance, and multi-class classifier and the tree based methods perform better than others.
AB - To solve the problem of emotional illiteracy in current e-Learning environment, researches on sentiment analysis now get more attentions. This paper focuses on recognizing emotion from interactive Chinese texts (ICTs). Through observation, firstly, characteristics of ICTs are discussed. Then two kinds of feature sets, frequency based feature set and interaction related feature set, are presented. Finally, the corresponding feature extraction and selection for ICTs are presented. To validate the feature sets and choose the best method of sentiment analysis, we carry out a number of experiments. The experiments' results show that, combining with syntax based feature set, frequency based feature set and interaction related feature set can improve algorithm classification performance, and multi-class classifier and the tree based methods perform better than others.
KW - Interactive Chinese Texts
KW - Sentiment Classification
KW - Turn
UR - https://www.scopus.com/pages/publications/84867028106
U2 - 10.1109/ICALT.2012.72
DO - 10.1109/ICALT.2012.72
M3 - 会议稿件
AN - SCOPUS:84867028106
SN - 9780769547022
T3 - Proceedings of the 12th IEEE International Conference on Advanced Learning Technologies, ICALT 2012
SP - 480
EP - 484
BT - Proceedings of the 12th IEEE International Conference on Advanced Learning Technologies, ICALT 2012
T2 - 12th IEEE International Conference on Advanced Learning Technologies, ICALT 2012
Y2 - 4 July 2012 through 6 July 2012
ER -