TY - GEN
T1 - An iterative emotion classification approach for microblogs
AU - Xu, Ruifeng
AU - Wang, Zhaoyu
AU - Xu, Jun
AU - Chen, Junwen
AU - Lu, Qin
AU - Wong, Kam Fai
PY - 2015/1/1
Y1 - 2015/1/1
N2 - The typical emotion classification approach adopts one-step singlelabel classification using intra-sentence features such as unigrams, bigrams and emotion words. However, single-label classifier with intra-sentence features cannot ensure good performance for short microblogs text which has flexible expressions. Target to this problem, this paper proposes an iterative multi-label emotion classification approach for microblogs by incorporating intra-sentence features, as well as sentence and document contextual information. Based on the prediction of the base classifier with intra-sentence features, the iterative approach updates the prediction by further incorporating both sentence and document contextual information until the classification results converge. Experimental results obtained by three different multi-label classifiers on NLP & CC2013 Chinese microblog emotion classification bakeoff dataset demonstrates the effectiveness of our iterative emotion classification approach.
AB - The typical emotion classification approach adopts one-step singlelabel classification using intra-sentence features such as unigrams, bigrams and emotion words. However, single-label classifier with intra-sentence features cannot ensure good performance for short microblogs text which has flexible expressions. Target to this problem, this paper proposes an iterative multi-label emotion classification approach for microblogs by incorporating intra-sentence features, as well as sentence and document contextual information. Based on the prediction of the base classifier with intra-sentence features, the iterative approach updates the prediction by further incorporating both sentence and document contextual information until the classification results converge. Experimental results obtained by three different multi-label classifiers on NLP & CC2013 Chinese microblog emotion classification bakeoff dataset demonstrates the effectiveness of our iterative emotion classification approach.
KW - Emotion Classification
KW - Iterative Classification
KW - Microblogs
UR - http://www.scopus.com/inward/record.url?scp=84942516138&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-18117-2_8
DO - 10.1007/978-3-319-18117-2_8
M3 - Conference article published in proceeding or book
SN - 9783319181165
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 104
EP - 113
BT - Computational Linguistics and Intelligent Text Processing - 16th International Conference, CICLing 2015, Proceedings
PB - Springer Verlag
T2 - 16th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2015
Y2 - 14 April 2015 through 20 April 2015
ER -