Methodological Implications of Employing Social Bigdata Analysis for Policy-Making : A Case of Social Media Buzz on the Startup Business

Abstract Submitted：October 26, 2015 1 st Revision：January 5, 2016 Accepted：January 7, 2016* 한국정보화진흥원 수석연구원, 정보시스템학 박사, 교신저자** (주)아르스프락시아 대표In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy- makers. Recently, bigdata anlalytics challenge traditional meth ods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the autho rs introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding governmen t’s policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-mak ing. Methodological and practical implications are discussed.