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http://dx.doi.org/10.9717/kmms.2014.17.6.671

An Extraction Method of Sentiment Infromation from Unstructed Big Data on SNS  

Back, Bong-Hyun (Dept. of Computer Engineering, Yeungnam University)
Ha, Ilkyu (Dept. of Computer Engineering, Yeungnam University)
Ahn, ByoungChul (Dept. of Computer Engineering, Yeungnam University)
Publication Information
Journal of Korea Multimedia Society / v.17, no.6, 2014 , pp. 671-680 More about this Journal
Abstract
Recently, with the remarkable increase of social network services, it is necessary to extract interesting information from lots of data about various individual opinions and preferences on SNS(Social Network Service). The sentiment information can be applied to various fields of society such as politics, public opinions, economics, personal services and entertainments. To extract sentiment information, it is necessary to use processing techniques that store a large amount of SNS data, extract meaningful data from them, and search the sentiment information. This paper proposes an efficient method to extract sentiment information from various unstructured big data on social networks using HDFS(Hadoop Distributed File System) platform and MapReduce functions. In experiments, the proposed method collects and stacks data steadily as the number of data is increased. When the proposed functions are applied to sentiment analysis, the system keeps load balancing and the analysis results are very close to the results of manual work.
Keywords
Big Data; Sentiment Analysis; SNS; Unstructed data analysis;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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