QQ客服 官方微博 反馈留言

	A topic model for building fine-grained domain-specific emotion lexicon
	Min Yang; Baolin Peng; Zheng Chen; Dingju Zhu; Kam-Pui Chow
	2014
会议名称	52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014
会议地点	Baltimore, MD, United states
英文摘要	Emotion lexicons play a crucial role in sentiment analysis and opinion mining. In this paper, we propose a novel Emotion-aware LDA (EaLDA) model to build a domainspecific lexicon for predefined emotions that include anger, disgust, fear, joy, sadness, surprise. The model uses a minimal set of domain-independent seed words as prior knowledge to discover a domainspecificlexicon, learning a fine-grained emotion lexicon much richer and adaptive to a specific domain. By comprehensive experiments, we show that our model can generate a high-quality fine-grained domain-specific emotion lexicon.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/6066]
专题	深圳先进技术研究院_数字所
作者单位	2014
推荐引用方式 GB/T 7714	Min Yang,Baolin Peng,Zheng Chen,et al. A topic model for building fine-grained domain-specific emotion lexicon[C]. 见:52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014. Baltimore, MD, United states.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。