TY - GEN
T1 - Weighted multi-label classification model for sentiment analysis of online news
AU - Li, Xin
AU - Xie, Haoran
AU - Rao, Yanghui
AU - Chen, Yanjia
AU - Liu, Xuebo
AU - Huang, Huan
AU - Wang, Fu Lee
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/3/3
Y1 - 2016/3/3
N2 - With the extensive growth of social media services, many users express their feelings and opinions through news articles, blogs and tweets/microblogs. To discover the connections between emotions evoked in a user by varied-scale documents effectively, the paper is concerned with the problem of sentiment analysis over online news. Different from previous models which treat training documents uniformly, a weighted multi-label classification model (WMCM) is proposed by introducing the concept of emotional concentration to estimate the weight of training documents, in addition to tackle the issue of noisy samples for each emotion. The topic assignment is also used to distinguish different emotional senses of the same word at the semantic level. Experimental evaluations using short news headlines and long documents validate the effectiveness of the proposed WMCM for sentiment prediction.
AB - With the extensive growth of social media services, many users express their feelings and opinions through news articles, blogs and tweets/microblogs. To discover the connections between emotions evoked in a user by varied-scale documents effectively, the paper is concerned with the problem of sentiment analysis over online news. Different from previous models which treat training documents uniformly, a weighted multi-label classification model (WMCM) is proposed by introducing the concept of emotional concentration to estimate the weight of training documents, in addition to tackle the issue of noisy samples for each emotion. The topic assignment is also used to distinguish different emotional senses of the same word at the semantic level. Experimental evaluations using short news headlines and long documents validate the effectiveness of the proposed WMCM for sentiment prediction.
KW - Emotional concentration
KW - Multi-label classification
KW - Sentiment analysis
UR - http://www.scopus.com/inward/record.url?scp=84964680938&partnerID=8YFLogxK
U2 - 10.1109/BIGCOMP.2016.7425916
DO - 10.1109/BIGCOMP.2016.7425916
M3 - Conference contribution
AN - SCOPUS:84964680938
T3 - 2016 International Conference on Big Data and Smart Computing, BigComp 2016
SP - 215
EP - 222
BT - 2016 International Conference on Big Data and Smart Computing, BigComp 2016
T2 - International Conference on Big Data and Smart Computing, BigComp 2016
Y2 - 18 January 2016 through 20 January 2016
ER -