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Frequency and Social Network Analysis of the Bible Data using Big Data Analytics Tools R

빅데이터 분석도구 R을 이용한 성경 데이터의 빈도와 소셜 네트워크 분석

  • Ban, ChaeHoon (Department of IT Management, Kosin University) ;
  • Ha, JongSoo (Department of Broadcasting & Image, Kyungnam College of Information & Technology) ;
  • Kim, Dong Hyun (Dept of Software, Dongseo University)
  • Received : 2019.10.24
  • Accepted : 2019.11.06
  • Published : 2020.02.29

Abstract

Big data processing technology that can store and analyze data and obtain new knowledge has been adjusted for importance in many fields of the society. Big data is emerging as an important problem in the field of information and communication technology, but the mind of continuous technology is rising. the R, a tool that can analyze big data, is a language and environment that enables information analysis of statistical bases. In this paper, we use this to analyze the Bible data. We analyze the four Gospels of the New Testament in the Bible. We collect the Bible data and perform filtering for analysis. The R is used to investigate the frequency of what text is distributed and analyze the Bible through social network analysis, in which words from a sentence are paired and analyzed between words for accurate data analysis.

데이터를 저장하고 분석하여 새로운 지식을 얻을 수 있는 빅데이터 처리기술은 사회의 여러 분야에서 중요성이 강조되고 있으며 정보통신기술 분야의 핵심 이슈로 부각되면서 관련 기술에 대한 관심이 증가하고 있다. 이러한 빅데이터를 분석할 수 있는 도구인 R은 통계 기반의 정보 분석을 가능하게 하는 언어와 환경이다. 본 논문에서는 이를 이용하여 성경데이터를 분석한다. 성경 중에서 신약성경의 4복음서의 데이터를 분석한다. 먼저 성경데이터를 수집하고 분석을 위한 필터링을 수행한다. 이후 R을 이용하여 어떠한 텍스트가 분포되어 있는지를 빈도 조사를 수행하며 정확한 데이터의 분석을 위해 한 문장에서 나오는 단어들을 쌍으로 표현하고 단어 간의 관계성을 분석하는 소셜 네트워크 분석을 통해 성경을 분석한다.

Keywords

References

  1. C. Ban, Y. Lee, D. Ahn, and Y. Kwak, "The Venture Business Starts News and SNS Big Data Analytics," in Proceeding of Korea Institute of Information and Communication Engineering 2017, pp. 311-314, 2017.
  2. Y. Hwang, J. Park, I. Moon, K. Kim, and O. Kwan, "(The)Box-office Success Factors of Films Utilizing Big Data-Focus on Laugh and Tear of Film Factors," Journal of Information and Communication Engineering, vol. 20, no. 6, pp. 1087-1095, 2016.
  3. C. Ban, D. Kim, and J. Ha, "Analysis of University Department Name using the R," Journal of Information and Communication Engineering, vol. 22, no. 6, pp. 829-834, 2018.
  4. H. Kim, "Big Data Case Study by Using R," M. S. theses, Hoseo University, Asan, Korea, 2014.
  5. Y. Oh, and E. Park, "Data visualization of airquality data using R software," Journal of the Korea Data & Information Science Society, vol. 26, no. 2, pp. 399-408, 2015. https://doi.org/10.7465/jkdi.2015.26.2.399
  6. C. Jang, J. Jang, S. Kim, H. Lee, and C. Lee, "A study on the efficient patent search process using big data analysis tool R," Journal of Korea Safety Management & Science, vol. 15, no. 4, pp. 289-294, 2013. https://doi.org/10.12812/ksms.2013.15.4.289
  7. Y. Kim, and C. Ban, "Analysis of the Bible Data using Big Data Analytics Tools R," in Proceeding of Korea Institute of Information and Communication Engineering 2015, pp. 349-352, 2015.