Social Big Data Analysis for Franchise Stores (프랜차이즈 스토어를 대상으로 한 소셜 빅데이터 분석 방법)

Hyeon Gyu Kim (김현규)

doi:10.9708/jksci.2021.26.08.039

Social Big Data Analysis for Franchise Stores

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2021, 26(8), pp.39-46
DOI : 10.9708/jksci.2021.26.08.039
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : June 10, 2021
Accepted : July 27, 2021
Published : August 31, 2021

Hyeon Gyu Kim ¹

¹삼육대학교

Accredited

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

Citation status

* References for papers published after 2023 are currently being built.

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KJCKorea
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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Social Big Data Analysis for Franchise Stores

ABSTRACT

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Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Social Big Data Analysis for Franchise Stores

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.