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Analyzing Sentiment in Student-Teacher Textual Comments Using Lexicon Based Approach

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dc.contributor.author Aung, Khin Zezawar
dc.contributor.author Myo, Nyein Nyein
dc.date.accessioned 2019-07-03T08:41:08Z
dc.date.available 2019-07-03T08:41:08Z
dc.date.issued 2018-02-22
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/357
dc.description.abstract Opinion mining, which is also known as Sentiment Analysis, is an interesting field to analyze people’s opinions, sentiments, attitudes and appraisals. There are several approaches to analyze the textual data using sentiment analysis. The unstructured textual feedback comments are very complex and the evaluation of these comments is a difficult task. Manual analysis of opinion result takes too long to determine. So, an automated textual analysis is performed using lexicon based approach to predict the teaching performance. Most of the existing sentiment lexicon can’t identify some words concerning with the educational domain. There is no teaching sentiment lexicon publicly available for educational domain. So, teaching sentiment lexicon is created for educational domain to get the polarity of words. The experimental results show that the proposed lexicon is more effective than other lexicons for educational domain. en_US
dc.language.iso en en_US
dc.publisher Sixteenth International Conferences on Computer Applications(ICCA 2018) en_US
dc.title Analyzing Sentiment in Student-Teacher Textual Comments Using Lexicon Based Approach en_US
dc.type Article en_US

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