Paper: Identifying Emotion Labels from Psychiatric Social Texts Using Independent Component Analysis

ACL ID C14-1080
Title Identifying Emotion Labels from Psychiatric Social Texts Using Independent Component Analysis
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

Accessing the web has been an efficient and effective means to acquire self-help knowledge when suf- fering from depressive problems. Many mental health websites have developed community-based ser- vices such as web forums and blogs for Internet users to share their depressive problems with other us- ers and health professionals. Other users or health professionals can then make recommendations in re- sponse to these problems. Such communications produce a large number of documents called psychiat- ric social texts containing rich emotion labels representing different depressive problems. Automatically identify such emotion labels can make online psychiatric services more effective. This study proposes a framework combining latent semantic analysis (LSA) and independent component analysi...