NDLI: Sentiment analysis in multi-scenarios: Using evolution strategies for optimization

Content Provider	IEEE Xplore Digital Library
Author	Heng-Li Yang Qing-Feng Lin
Copyright Year	2013
Description	Author affiliation: MIS Dept., Nat. Cheng-Chi Univ., Taipei, Taiwan (Heng-Li Yang; Qing-Feng Lin)
Abstract	With the developing of blog, mircoblog and social networking sites, researchers and practitioners have paid more attentions to how to accurately get useful positive/negative evaluation information from those web opinion articles which have different writing styles. This is so-called opinion mining and sentiment analysis. However, very few sentiment analysis studies focused on multi-scenarios problem. This study collected some Chinese sentences from one movie blog at Taiwan, and conducted an experiment to infer those authors' sentiment. We chose two different scenarios, general and horror. After collecting the inferences of readers, we applied evolutionary computing strategies to optimize the tables of basic emotion weights in two different scenarios. The findings indicate that our approach would have better correct rates than past research which considered only one general scenario. Through these findings, we can understand what are people concerned in different scenarios.
Starting Page	1230
Ending Page	1233
File Size	645811
Page Count	4
File Format	PDF
ISBN	9781479902606
DOI	10.1109/ICMLC.2013.6890777
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Abstracts Ontologies Ear Sentiment Analysis Affective Computing Multi-Scenarios Evolution Strategies
Content Type	Text
Resource Type	Article

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