Aspect identification and sentiment analysis based on NLP

Author

Li Zhang ; Weiran Xu ; Si Li

Author_Institution

Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2012

fDate

21-23 Sept. 2012

Firstpage

660

Lastpage

664

Abstract

This paper proposes method for aspect identification and sentiment analysis. This paper deals with the problem of sentence level. We use semantic syntax tree to extract NP nodes, a method based on slack to identify aspect and mini-support function to narrow aspect; to analyze the sentiment for the aspect we use dictionary-based method. Experimental results show that the proposed approach achieves the state-of-the-art.

Keywords

computational linguistics; data mining; dictionaries; natural language processing; tree searching; NLP; NP nodes extraction; aspect identification; dictionary based method; semantic syntax tree; sentence level; sentiment analysis; Data mining; Feature extraction; Internet; Motion pictures; Syntactics; Vocabulary; Aspect identification; Mini-support; Semantic syntax; Sentiment analysis; Sentiment dictionary; Slack;

fLanguage

English

Publisher

ieee

Conference_Titel

Network Infrastructure and Digital Content (IC-NIDC), 2012 3rd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4673-2201-0

Type

conf

DOI

10.1109/ICNIDC.2012.6418838

Filename

6418838

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3052850