Title
Learning from context: A mutual reinforcement model for Chinese microblog opinion retrieval.
Abstract
This study addresses the problem of Chinese microblog opinion retrieval, which aims to retrieve opinionated Chinese microblog posts relevant to a target specified by a user query. Existing studies have shown that lexicon-based approaches employed online public sentiment resources to rank sentimentwords relying on the document features. However, this approach could not be effectively applied to microblogs that have typical user-generated content with valuable contextual information: “user–user” interpersonal interactions and “user–post/comment” intrapersonal interactions. This contextual information is very helpful in estimating the strength of sentiment words more accurately. In this study, we integrate the social contextual relationships among users, posts/comments, and sentiment words into a mutual reinforcement model and propose a unified three-layer heterogeneous graph, on which a random walk sentiment word weighting algorithm is presented to measure the strength of opinion of the sentiment words. Furthermore, the weights of sentiment words are incorporated into a lexicon-based model for Chinese microblog opinion retrieval. Comparative experiments are conducted on a Chinese microblog corpus, and the results show that our proposed mutual reinforcement model achieves significant improvement over previous methods.
Year
DOI
Venue
2018
10.1007/s11704-016-6163-5
Frontiers Comput. Sci.
Keywords
Field
DocType
opinion retrieval,sentiment words,lexicon weighting,mutual reinforcement model
Intrapersonal communication,Weighting,Computer science,Natural language processing,Artificial intelligence,Graph,World Wide Web,Contextual information,Social media,Interpersonal communication,Microblogging,Lexicon,Reinforcement,Machine learning
Journal
Volume
Issue
ISSN
12
4
2095-2228
Citations 
PageRank 
References 
3
0.37
17
Authors
5
Name
Order
Citations
PageRank
Jingjing Wei131.72
Xiangwen Liao291.79
Houdong Zheng361.43
Guolong Chen45211.10
Xueqi Cheng53148247.04