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A Study on the Application of Opinion Mining Based on Big Data  

Kim, Ji Sook (Dept. of Informational Statistics, Korea University)
Jin, Seohoon (Dept. of Informational Statistics, Korea University)
Publication Information
Journal of the Korean Data Analysis Society / v.15, no.1B, 2013 , pp. 101-113 More about this Journal
Abstract
With the advent of smart phones and social media, the big data issue has spread throughout the industry. Big data analysis technique has become an important factor to increase the competitiveness of enterprises. How to analyze and utilize the big data can influence the company's future success. However, the value of big data is only a handful. Thus, extraction its value from big data will measure the success or failure of companies. In order to analyze large amounts of data into meaningful data advanced techniques are needed. In this paper, we learn about big data and big data analysis methods. Opinion mining through consumer reaction expressed in social media can be a leading indicator of corporate image that looked. Comments on Twitter for supermarkets are collected and companies were analyzed with either a positive or negative image.
Keywords
Big Data; Opinion Mining; Word Cloud; network of term;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 McKinsey (2011). Big Data : The Next Frontier for Innovation, Competition, and Productivity, http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation
2 Gartner Inc. (2011). Hadoop and MapReduce : Big Data Analytics, http://info.cloudera.com/GartnerReportHadoop January 2011.html
3 IDC (2011). IDC's Worldwide Big Data Taxonomy, http://www.idc.com/getdoc.jsp?containerId=231099
4 Kim, J. (2012a). Big Data utilization and related technical discussion, Journal of the Korea Contents Association, 10(1), 34-40. (in Korean).
5 Kim, J. (2012b). A Study on Application of Big Data and Technologies of Analysis, Thesis for the Degree of Master, Korea University. (in Korean).
6 Oh, H., Cho, S., Kang, C., Lim, D. (2010). Fashion Company's Claim Data Analysis Using Text Mining, Journal of the Korean Data Analysis Society, 12(1), 297-306. (in Korean).
7 Oh, S., Jin, S. (2012). A Study on Analysis of Internet Shopping Mall Customers' Reviews by Text Mining, Journal of the Korean Data Analysis Society, 14(1), 125-138. (in Korean).
8 Park, H., Lee, Y. (2009). A Mixed Text Analysis of User Comments on a Portal Site : The 'BBK Scandal' in the 2007 Presidential Election of South Korea, Journal of the Korean Data Analysis Society, 11(2), 731-744. (in Korean).
9 Park, Y., Ko, Y., Kim, J. (2012). R Packages for Parallel Computing and their Performance Evaluation, Journal of the Korean Data Analysis Society, 14(4), 1951-1962. (in Korean).
10 SAS Publishing (2010). Text Analytics with SAS Text Miner, SAS Institute Inc., Cary, NC, USA.
11 http://www.bicdata.com/
12 http://www.cs.uic.edu/-liub/FBS/sentiment-analysis.html
13 http://www.inside-r.org/howto/mining-twitter-airline-consumer-sentiment
14 http://www.rdatamining.com/examples/text-mining
15 Cho, S. (2011). Big Data era of technology, KT Advanced Institute of Technology Report. (in Korean).