TY - GEN
T1 - Automatically Labelling Sentiment-bearing Topics with Descriptive Sentence Labels
AU - Barawi, Mohamad Hardyman Bin
AU - Lin, Chenghua
AU - Siddharthan, Advaith
PY - 2017
Y1 - 2017
N2 - In this paper, we propose a simple yet effective approach for automatically labelling sentiment-bearing topics with descriptive sentence labels. Specifically, our approach consists of two components: (i) a mechanism which can automatically learn the relevance to sentiment-bearing topics of the underlying sentences in a corpus; and (ii) a sentence ranking algorithm for label selection that jointly considers topic-sentence relevance as well as aspect and sentiment co-coverage. To our knowledge, we are the first to study the problem of labelling sentiment-bearing topics. Our experimental results show that our approach outperforms four strong baselines and demonstrates the effectiveness of our sentence labels in facilitating topic understanding and interpretation.
AB - In this paper, we propose a simple yet effective approach for automatically labelling sentiment-bearing topics with descriptive sentence labels. Specifically, our approach consists of two components: (i) a mechanism which can automatically learn the relevance to sentiment-bearing topics of the underlying sentences in a corpus; and (ii) a sentence ranking algorithm for label selection that jointly considers topic-sentence relevance as well as aspect and sentiment co-coverage. To our knowledge, we are the first to study the problem of labelling sentiment-bearing topics. Our experimental results show that our approach outperforms four strong baselines and demonstrates the effectiveness of our sentence labels in facilitating topic understanding and interpretation.
UR - http://www.scopus.com/inward/record.url?scp=85021717650&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-59569-6_38
DO - 10.1007/978-3-319-59569-6_38
M3 - Published conference contribution
SN - 9783319595689
VL - 10260 LNCS
T3 - Lecture Notes in Computer Science
SP - 299
EP - 312
BT - The 22nd International Conference on Natural Language & Information Systems (NLDB)
PB - Springer
CY - Belgium
T2 - 22nd International Conference on Natural Language & Information Systems
Y2 - 21 June 2017 through 23 June 2017
ER -