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Performing sentiment analysis in Bangla microblog posts

Show simple item record Chowdhury, Shaika Chowdhury, Wasifa 2017-01-04T10:26:54Z 2017-01-04T10:26:54Z 2014
dc.identifier.citation Chowdhury, S., & Chowdhury, W. (2014). Performing sentiment analysis in bangla microblog posts. Paper presented at the 2014 International Conference on Informatics, Electronics and Vision, ICIEV 2014, doi:10.1109/ICIEV.2014.6850712 en_US
dc.identifier.isbn 978-147995179-6
dc.description This conference paper was presented in the International Conference on Informatics, Electronics and Vision, ICIEV 2014; Dhaka; Bangladesh; 23 May 2014 through 24 May 2014 [© 2014 IEEE] The conference paper's definite version is available at: en_US
dc.description.abstract Much of the research work on sentiment analysis has been carried out in the English language, but work in Bangla is limited to only news corpus and blogs. Microblogging sites are becoming a valuable source for publishing huge volumes of user-generated information, as users express their views, opinions, and sentiments over various topics. In this paper, we aim to automatically extract the sentiments or opinions conveyed by users from Bangla microblog posts and then identify the overall polarity of texts as either negative or positive. We use a semi-supervised bootstrapping approach for the development of the training corpus which avoids the need for labor intensive manual annotation. For classification, we use Support Vector Machine (SVM) and Maximum Entropy (MaxEnt) and do a comparative analysis on the performance of these two machine learning algorithms by experimenting with a combination of various sets of features. en_US
dc.language.iso en en_US
dc.publisher © 2014 IEEE Computer Society en_US
dc.subject Bangla microblog posts en_US
dc.subject Maximum entropy en_US
dc.subject Semi-supervised bootstrapping en_US
dc.subject Sentiment analysis en_US
dc.subject Support vector machine en_US
dc.title Performing sentiment analysis in Bangla microblog posts en_US
dc.type Conference paper en_US
dc.description.version Published
dc.contributor.department Department of Computer Science and Engineering, BRAC University

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