Identifying Transferable Information Across Domains for Cross-domain Sentiment Classification

Raksha Sharma, Pushpak Bhattacharyya, Sandipan Dandapat, Himanshu Sharad Bhatt


Abstract
Getting manually labeled data in each domain is always an expensive and a time consuming task. Cross-domain sentiment analysis has emerged as a demanding concept where a labeled source domain facilitates a sentiment classifier for an unlabeled target domain. However, polarity orientation (positive or negative) and the significance of a word to express an opinion often differ from one domain to another domain. Owing to these differences, cross-domain sentiment classification is still a challenging task. In this paper, we propose that words that do not change their polarity and significance represent the transferable (usable) information across domains for cross-domain sentiment classification. We present a novel approach based on χ2 test and cosine-similarity between context vector of words to identify polarity preserving significant words across domains. Furthermore, we show that a weighted ensemble of the classifiers enhances the cross-domain classification performance.
Anthology ID:
P18-1089
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Iryna Gurevych, Yusuke Miyao
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
968–978
Language:
URL:
https://aclanthology.org/P18-1089
DOI:
10.18653/v1/P18-1089
Bibkey:
Cite (ACL):
Raksha Sharma, Pushpak Bhattacharyya, Sandipan Dandapat, and Himanshu Sharad Bhatt. 2018. Identifying Transferable Information Across Domains for Cross-domain Sentiment Classification. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 968–978, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Identifying Transferable Information Across Domains for Cross-domain Sentiment Classification (Sharma et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-1089.pdf
Presentation:
 P18-1089.Presentation.pdf
Video:
 https://aclanthology.org/P18-1089.mp4