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http://dx.doi.org/10.9708/jksci.2014.19.4.043

An Ontology-based Analysis of Wikipedia Usage Data for Measuring degree-of-interest in Country  

Kim, Hyon Hee (Dept. of Information and Statistics, Dongduk Women's University)
Jo, Jinnam (Dept. of Information and Statistics, Dongduk Women's University)
Kim, Donggeon (Dept. of Information and Statistics, Dongduk Women's University)
Publication Information
Journal of the Korea Society of Computer and Information / v.19, no.4, 2014 , pp. 43-53 More about this Journal
Abstract
In this paper, we propose an ontology-based approach to measuring degree-of-interest in country by analyzing wikipedia usage data. First, we developed the degree-of-interest ontology called DOI ontology by extracting concept hierarchies from wikipedia categories. Second, we map the title of frequently edited articles into DOI ontology, and we measure degree-of-interest based on DOI ontology by analyzing wikipedia page views. Finally, we perform chi-square test of independence to figure out if interesting fields are independent or not by country. This approach shows interesting fields are closely related to each country, and provides degree of interests by country timely and flexibly as compared with conventional questionnaire survey analysis.
Keywords
Analysis of Wikipedia Usage Data; Ontology-based Analysis; Degree-of-Interest Ontology; Measuring degree-of-interest by fields;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 R. Pappu, P. Quester, and G. R. W. Cooksey, "Country Image and Consumer-Based Brand Equity: Relationships and Implications for International Marketing." Journal of International Business Studies, Vol. 38, No. 5, pp. 726-745, June, 2007.   DOI   ScienceOn
2 S. Anholt, "Anholt Nation Brands Index: How Does the World See America?" Journal of Advertising Research, Vol. 45, No. 3, pp. 296-304, sept. 2005.
3 M. Ghiassi, J. Skinner and D. Zimbra, "Twitter Brand Sentiment Analysis: A Hybrid System Using n-gram Analysis and Dynamic Artificial Neural Network", Expert Systems with Applications, Vol. 40, pp. 6266-2686, Nov. 2013.   DOI   ScienceOn
4 M. M. Mostafa, "More than Words: Social Networks' Text Mining for Consumer Brand Sentiments", Expert Systems with Applications, Vol. 40, pp. 4241-4251, Aug. 2013.   DOI   ScienceOn
5 Wikipedia, http://en.wikipedia.org/
6 D. A. Aacker, "Managing Brand Equity", The Free Press: New York, Sept. 1991.
7 T. R. Gruber, "A Translation Approach to Portable Ontology Specifications", Knowledge Acquisition, Vol. 5, No. 2, pp. 199-220, June, 1993.   DOI   ScienceOn
8 H. H. Kim, "A Tag-based Music Recommendation Using UniTag Ontology", Journal of the Korea Society of Computer and Information, Vol. 17, No. 11, pp. 133-140, Nov. 2012.   과학기술학회마을   DOI   ScienceOn
9 W. Wong, W. Liu and M. Bennamoun, "Ontology Learning from Text: A Look Back and into the Future", ACM Computing Surveys, Vol. 44, pp.1-35, Aug. 2012.
10 F. M. Suchanek, G. Kasneci and G. Weikum, "YAGO: A Core of Semantic Knowledge Unifying WordNet and Wikipedia", In Proc. of World Wide Web Conference, pp. 697-706, Alberta, Canada, May, 2007.
11 M. Morsey et al., "DBpedia and the Live Extraction of Structured Data fromWikipedia", Electronic Library and Information Systems, Vol. 46, No. 2, pp. 157-181, June, 2012.   DOI   ScienceOn
12 S. P. Ponzetto and M. Strube, "Knowledge Derived From Wikipedia For Computing Semantic Relatedness", Journal of Artificial Intelligence Research, Vol. 30, pp. 181-212, Oct. 2007.
13 H. S. Moat et al., "Quantifying Wikipedia Usage Patterns Before Stock Market Moves", Scientific Reports, Vol. 3, No. 1801, pp. 1-5, May, 2013.
14 P. Kotler and D. Getner, "Country as brand, product, and beyond: A Place Marketing and Brand Management Perspective", Journal of Brand Management, Vol. 9, No. 4, pp. 249-261, Jan. 2002.   DOI
15 Condor, http://www.ickn.org/condor.html