DocumentCode
3539784
Title
A comparative analysis of opinion mining and sentiment classification in non-english languages
Author
Medagoda, Nishantha ; Shanmuganathan, Subana ; Whalley, Jason
Author_Institution
Auckland Univ. of Technol., Auckland, New Zealand
fYear
2013
fDate
11-15 Dec. 2013
Firstpage
144
Lastpage
148
Abstract
In the past decade many opinion mining and sentiment classification studies have been carried out for opinions in English. However, the amount of work done for non-English text opinions is very limited. In this review, we investigate opinion mining and sentiment classification studies in three non-English languages to find the classification methods and the efficiency of each algorithm used in these methods. It is found that most of the research conducted for non-English has followed the methods used in the English language with only limited usage of language specific properties, such as morphological variations. The application domains seem to be restricted to particular fields and significantly less research has been conducted in cross domains.
Keywords
behavioural sciences computing; data mining; pattern classification; text analysis; language specific properties; morphological variations; nonEnglish languages; nonEnglish text opinions; opinion mining; sentiment classification; Accuracy; Algorithm design and analysis; Blogs; Classification algorithms; Data mining; Machine learning algorithms; Support vector machines; Machine Learning; Natural Language processing; Text mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in ICT for Emerging Regions (ICTer), 2013 International Conference on
Conference_Location
Colombo
Print_ISBN
978-1-4799-1275-9
Type
conf
DOI
10.1109/ICTer.2013.6761169
Filename
6761169
Link To Document