1. DWWP: Domain-specific new words detection and word propagation system for sentiment analysis in the tourism domain
- Author
-
Luyao Zhu, Yuanchun Zheng, Wei Li, Yong Shi, and Kun Guo
- Subjects
Information Systems and Management ,Computer science ,business.industry ,05 social sciences ,Sentiment analysis ,Unstructured data ,02 engineering and technology ,Mutual information ,computer.software_genre ,Lexicon ,Management Information Systems ,Domain (software engineering) ,Similarity (network science) ,Artificial Intelligence ,0502 economics and business ,0202 electrical engineering, electronic engineering, information engineering ,Graph (abstract data type) ,050211 marketing ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,computer ,Software ,Word (computer architecture) ,Natural language processing - Abstract
Online travel has developed dramatically during the past three years in China. This results in a large amount of unstructured data like tourism reviews from which it is hard to extract useful knowledge. In this paper, a DWWP system consisting of domain-specific new words detection (DW) and word propagation (WP) is presented. DW deals with the negligence of user-invented new words and converted sentiment words by means of AMI (Assembled Mutual Information). Inspired by social networks, the new method WP incorporates manually calibrated sentiment scores, semantic and statistical similarity information, which improves the quality of sentiment lexicon in comparison with existing data-driven methods. Experimental results show that DWWP improves seventeen percentage points compared with graph propagation and four percentage points compared with label propagation in terms of accuracy on Dataset I and Dataset II, respectively.
- Published
- 2018