[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2021.26.08.039

Social Big Data Analysis for Franchise Stores

Kim, Hyeon Gyu (Div. of Computer Science and Engineering, Sahmyook University)

Publication Information

Journal of the Korea Society of Computer and Information / v.26, no.8, 2021 , pp. 39-46 More about this Journal

Abstract

When conducting social big data analysis for franchise stores, reviews of multiple branches of a franchise can be collected together, from which analysis results can be distorted significantly. To improve its accuracy, it should be possible to filter reviews of other branches properly which are not subject to the analysis. This paper presents a method for social big data analysis which reflects characteristics of franchise stores. The proposed method consists of search key configuration and review filtering. For the former, the open data provided by Small Business Promotion Agency is used to extract region names for collecting reviews more accurately. For the latter, open search APIs provided by Naver or Kakao are used to obtain franchise branch information for filtering reviews of other branches that are not subject to analysis. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that the accuracy of the proposed review filtering was 93.6% on the average.

Keywords

Big data analysis; Social reviews; Franchise analysis; Open data; Review filtering;

Citations & Related Records

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