Search Word(s) in Title, Keywords, Authors, and Abstract:
Shi Dong
Microblog Sentiment Analysis Method Based on Spectral Clustering
Shi Dong, Xingang Zhang and Ya Li
Page: 727~739, Vol. 14, No.3, 2018
10.3745/JIPS.04.0076
Keywords: Machine Learning, RDM, Sentiment Analysis, Spectral Cluster
Show / Hide Abstract
Microblog Sentiment Analysis Method Based on Spectral Clustering
Shi Dong, Xingang Zhang and Ya Li
Page: 727~739, Vol. 14, No.3, 2018

Keywords: Machine Learning, RDM, Sentiment Analysis, Spectral Cluster
Show / Hide Abstract
This study evaluates the viewpoints of user focus incidents using microblog sentiment analysis, which has
been actively researched in academia. Most existing works have adopted traditional supervised machine
learning methods to analyze emotions in microblogs; however, these approaches may not be suitable in
Chinese due to linguistic differences. This paper proposes a new microblog sentiment analysis method that
mines associated microblog emotions based on a popular microblog through user-building combined with
spectral clustering to analyze microblog content. Experimental results for a public microblog benchmark
corpus show that the proposed method can improve identification accuracy and save manually labeled time
compared to existing methods.