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http://dx.doi.org/10.6109/jkiice.2015.19.4.780

The Sensitivity Analysis for Customer Feedback on Social Media  

Song, Eun-Jee (Dept. of Computer Science, Namseoul University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.4, 2015 , pp. 780-786 More about this Journal
Abstract
Social media, such as Social Network Service include a lot of spontaneous opinions from customers, so recent companies collect and analyze information about customer feedback by using the system that analyzes Big Data on social media in order to efficiently operate businesses. However, it is difficult to analyze data collected from online sites accurately with existing morpheme analyzer because those data have spacing errors and spelling errors. In addition, many online sentences are short and do not include enough meanings which will be selected, so established meaning selection methods, such as mutual information, chi-square statistic are not able to practice Emotional Classification. In order to solve such problems, this paper suggests a module that can revise the meanings by using initial consonants/vowels and phase pattern dictionary and meaning selection method that uses priority of word class in a sentence. On the basis of word class extracted by morpheme analyzer, these new mechanisms would separate and analyze predicate and substantive, establish properties Database which is subordinate to relevant word class, and extract positive/negative emotions by using accumulated properties Database.
Keywords
Social media; Big Data; Customer feedback; Sensitivity analysis; Morphological analysis;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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