A lot of news articles in the portal

blog and forums always have their own emotional orientations and sentiment key sentence identification plays an important role in distinguishing emotional orientation of one article

supervising social trends and public sentiment state.The traditional lexicon-based methods totally depended on lexical semantics and did not excavate the implied syntactic structure.So a hybrid method of sentiment key sentence identification based on lexical semantics and syntactic dependency is proposed in this paper.This approach first gets lexical semantics knowledge from emotion lexicon expansion and keywords lexicon construction

and then this paper proposes a novel dependency templates extraction algorithm for syntactic dependency information to build a dependency knowledge base

finally we regard sentiment key sentence identification as a classification task and perform identification through different groups of features.Experimental results on COAE2014 dataset show that this approach notably outperforms other baselines of sentiment key sentence identification on precision and recall.