Cluster-level emotion pattern matching for cross-domain social emotion classification

Endong ZHU, Yanghui RAO*, Haoran XIE, Yuwei LIU, Jian YIN, Fu Lee WANG

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

3 Citations (Scopus)


This paper addresses the task of cross-domain social emotion classification of online documents. The cross-domain task is formulated as using abundant labeled documents from a source domain and a small amount of labeled documents from a target domain, to predict the emotion of unlabeled documents in the target domain. Although several cross-domain emotion classification algorithms have been proposed, they require that feature distributions of different domains share a sufficient overlapping, which is hard to meet in practical applications. This paper proposes a novel framework, which uses the emotion distribution of training documents at the cluster level, to alleviate the aforementioned issue. Experimental results on two datasets show the effectiveness of our proposed model on cross-domain social emotion classification.

Original languageEnglish
Title of host publicationProceedings of the 2017 ACM on Conference on Information and Knowledge Management
Place of PublicationUnited States
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Print)9781450349185
Publication statusPublished - 6 Nov 2017
Externally publishedYes
Event26th ACM International Conference on Information and Knowledge Management - Pan Pacific Singapore Hotel, Singapore, Singapore
Duration: 6 Nov 201710 Nov 2017

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings
VolumePart F131841


Conference26th ACM International Conference on Information and Knowledge Management
Abbreviated titleCIKM 2017
Internet address

Bibliographical note

This research was supported by the National Natural Science Foundation of China (61502545, 61472453, U1401256, U1501252, U1611264), Research Grants Council of Hong Kong Special Administrative Region, China (UGC/FDS11/E03/16), and the Internal Research Grant (RG 66/2016-2017) of The Education University of Hong Kong.


  • Clustering
  • Cross-domain classification
  • Emotion detection


Dive into the research topics of 'Cluster-level emotion pattern matching for cross-domain social emotion classification'. Together they form a unique fingerprint.

Cite this