Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

Framework for Measuring Dynamic Influence Index & Influence Factors using Social Data on Facebook

페이스북 소셜 데이터를 이용한 동적 영향 요인 및 영향력 측정 방법에 관한 프레임워크

  • Koh, Seoung-hyun (Dept. of Knowledge Service of Hansung University) ;
  • You, Yen-yoo (Department of Knowledge Service & Consulting of Hansung University)
  • 고승현 (한성대학교 지식서비스&컨설팅학과) ;
  • 유연우 (한성대학교 지식서비스 & 컨설팅학과)
  • Received : 2016.08.01
  • Accepted : 2016.10.20
  • Published : 2016.10.28
Download PDF
⟨ Previous Next ⟩

Abstract

The explosive growth of social networking services based on smart devices popularize these relationships and activities online in accordance with the far larger impact of this on the real life offline, the interest and importance for the online activity is increasing. In this study, factors affecting the SNS activity are defined by object, user, influence direction, influence distance and proposed a method to measure organic terms in effect between the SNS users. Influence Direction and Influence Strength (or Distance) are elaborated by using the existing influence measurement element such as structured data - the number of friends, the difference between the number of contacts - and the new influence measurement element such as unstructured data - gap between the former time and the latter time, preference and type of response behavior - that occur in social network service. In addition, the system for collecting and analysing data for measuring influence from social network service and the process model on the method for measuring influence is tested by using sample data on Facebook and explained the implementation probability.

스마트기기 대중화에 따른 소셜 네트워크 서비스의 폭발적인 증가로 온라인상의 관계와 활동이 오프라인상의 실생활까지 영향을 미침에 따라 온라인상의 소셜 네트워크 활동에 대한 관심과 중요성이 지속적으로 증가하고 있다. 본 연구에서는 SNS 활동에 영향을 미치는 요소를 대상(object, 사용자(User), 영향력 방향(Influence direction), 영향력 강도(Influence distance) 4가지 요소로 정의하고 SNS 사용자 상호간 영향을 유기적 관점에서 측정하는 방법을 제안하였다. 기존 영향력 측정 요소를 반응횟수, 친구의 수, 접촉횟수 등 정형 데이터와 원인시간과 반응시간의 차이, 호감도, 반응의 유형 등 비정형 데이터까지 확대하여 영향력 방향(Influence Directio)과 영향력 강도(Influence Strength or Distance)의 측정 기법을 정교화 하였다. 또한, 영향력 측정을 위한 data를 수집하고 분석하는 시스템과 facebook으로 수집한 sample data를 이용한 영향력 측정 기법 프로세스를 실험하고 구현 가능성을 설명하였다.

Keywords

References

  1. Su-Young Pi, "Educational Utilization of Smart Devices in the Convergence Education Era," Journal of Digital Convergence, Vol. 13, No. 6, pp. 29-37, 2015. https://doi.org/10.14400/JDC.2015.13.6.29
  2. Yun-hee Lee, "Current status and major issues of Korean social network services," Seoul: Korea Internet and Security Agency, Korea, 2014.
  3. Seung-Ock Jang and Ho-Sun Heon, "A Study on the Condition of Prevention System and Convergence Policy for Smart Media Addiction," Journal of Digital Convergence, Vol. 13, No. 8, pp. 33-41, 2015.
  4. Seung Ho Cho and Sang-Hoon Cho, "A Cross- Cultural Study of the Product Opinion Leaders' Communication Activity on Facebook," Journal of Digital Convergence, Vol. 12, No. 8, pp. 67-76, 2014. https://doi.org/10.14400/JDC.2014.12.8.67
  5. J. Clyde Mitchell, "Social Networks," Annual Review of Anthropology, Vol. 3, pp. 279-299, 1974. https://doi.org/10.1146/annurev.an.03.100174.001431
  6. Jae Subp Oh, Kyoung Jun Lee, Jae Kyeong Kim, "Design and Analysis of Ubiquitous Social Network Management Service Model: u-Recruiting Service Model," Information Systems Review, Vol. 18, No. 1, pp. 1-23, 2016.
  7. Lee, Won Ho and Park, Jae Wan, "An Approach to Visualizing a Social Network Service Using a Blob Algorithm - Focusing on User Profile Data." Journal of Digital Design, Vol. 13, No. 4, pp. 465-476, 2013. https://doi.org/10.17280/jdd.2013.13.4.046
  8. Sun Hee Jang and Seok Hyun Jang, "A Framework for Visualizing Social Network Influence," Journal of Korea Multimedia Society, Vol. 12, No. 1, pp. 139-146, 2009.
  9. Kwak Mijun and Kim Youngmi, "A Study of Influence on Adolescent Psychological Well-Being - Focusing on Strengths of Family Life and Satisfaction with School Life in the IT-based Society," Journal of Digital Convergence, Vol. 11, No. 3, pp. 49-57, 2013. https://doi.org/10.14400/JDPM.2013.11.12.49
  10. Werner Raub and Jeroen Weesie, "Reputation and Efficiency in Social Interactions: An Example of Network Effects," American Journal of Sociology, Vol. 96, No. 3, pp. 626-654, 1990. https://doi.org/10.1086/229574
  11. Gerald R. Salancik and Jeffrey Pfeffer, "A Social Information Processing Approach to Job Attitudes and Task Design," Administrative Science Quarterly, Vol. 23, No. 2, pp. 224-253, 1978. https://doi.org/10.2307/2392563
  12. Gary S. Becker, "A Theory of Social Interactions," Journal of Political Economy, Vol. 82, No. 6, pp. 1063-1093, 1974. https://doi.org/10.1086/260265
  13. Jung-Yul Jo, "Power of SNS Authenticity on Company Reputation," Journal of Digital Convergence, Vol. 13, No. 2, pp. 73-81, 2015. https://doi.org/10.14400/JDC.2015.13.2.73
  14. Joseph B. Walther, "Interpersonal Effects in Computer-Mediated Interaction: A Relational Perspective," Communication Research, Vol. 19, No. 1, pp. 52-90, 1992 https://doi.org/10.1177/009365092019001003
  15. Hyun-Jee Park, "The Influence of Tourist's Ethical Consumption Concept on Fair Tourism Attitude and Purchasing Intention of Fair Tourism on Tourism Social Media -Considering Risk Perception of Ethical Consumption as the Mediator-," Journal of Digital Convergence, Vol. 14, No. 1, pp. 83-90, 2016.
  16. Ji-Suk Kim, "The ego resilience, social support, awareness of the instructional outcome of pre-service teacher in university classes using SNS(Social Network Service," Journal of Digital Convergence, Vol. 14, No. 2, pp. 31-39, 2016. https://doi.org/10.14400/JDC.2016.14.2.31
  17. Fredrick Erlandsson, Anton Brog, Henric Johnson, and Protr Brodka, "Predicting user participation in social media" Advances in Network Science, Vol. 9564 of the series Lecture Notes in Computer Science, pp. 126-135, 2016.
  18. Kwang-Soo Seol, Jeong-Dong Kim, Hyung-Nam Shim and Doo-Kwan Baik, "Intimacy Measurement Method and Experiment between Social Network Service Users," Journal of KISS : Information Networking, Vol. 39, No. 4, pp. 335-341, 2012.
  19. Soo-Seok Suh and Jong-Ho Lee, "The Effect of Structure and Relation of Social Networks on Purchase Intention of Social Commerce Sites," The e-Business Studies, Vol. 12, No. 3, pp. 105-125, 2011. https://doi.org/10.15719/geba.12.3.201109.105
  20. Seung-Hee Lee and Young-Ho Park, "An Influence Measuring Technique for Social Network Activities," Journal of KISS : Databases, Vol. 39, No. 1, pp. 43-52, 2012.
  21. Ho-Sung Park, Hae-Un Kwok, Mi-Young Cha and Soo-Bok Moon, "Influentials Ranking in Social Networks," Communications of the Korean Institute of Information Scientists and Engineers, Vol. 28, No. 3, pp. 24-30, 2010.
  22. Ji Hye Park, Bo Hyun Kim, Myung Joon Lee and Yung Keun Kwon, "TwitNet : Cytoscape Plugin for Visualizing Relation between Twitter Users," Korea Computer Congress 2010, Vol. 37, No. 1, pp. 316-321, 2010.
  23. M. Cha, H. Haddadi, F. Benevenuto, and K. P. Gummad, "Measuring user influence on twitter: The million follower fallacy," In 4th Int'l AAAI Conference on Weblogs and Social Media, Washington, DC, 2010.
  24. Eui-Jong Lee, Jung-dong Kim and Doo-kwon Baek, "Measuring Influence of Twitter Contents Using In-Degrees" Korea Information Science Journal, Vol. 40, pp. 170-172, 2013.
  25. Yun Liu and Fei Xiang, "A method of measuring user influence in MicroBlog," Journal of Convergence Information Technology, Vol. 16, No. 10, pp. 242-250, 2011.
  26. K. Hazel Kwon, Michael A. Stefanone, and George A. Barnett, "Social Network Influence on Online Behavioral Choices Exploring Group Formation on Social Network Sites." American Behavioral Scientist September 2014, pp 1345-1360, 2014.
  27. Aihua Wang, Siu Cheung Kong, "A Study of Relations between Students' CMC Behaviors and Perceived Effects of CMC on Learning for Incorporating CMC in Hybrid Learning" Hybrid Learning, Vol. 6837, pp. 95-104, 2011. https://doi.org/10.1007/978-3-642-22763-9_9
  28. Minkyoung Kim and Byoung-Tak Zhang, "A Social Influence Model based on Starbucks Networks." Journal of KIISE 2008 Fall, Vol 35, No. 2, pp 101-102, 2008.
  29. Jin-hyung Lee, "Diffusion and trends of SNS(Social Network Service)". Seoul: Korea Communications Agency, 2012.
  30. Yun-hwa Kim, "An analysis on SNS (social network service) usage patterns and behaviors". Seoul: Korea Information Society Development Institute, 2015.
  31. John Scott, "Social network analysis". SAGE Publications Ltd, London UK, 2013.
  32. Yong-hak Kim, "SNS Theory". Bakyoungsa, Seoul, Korea, 2011.
  33. D. Tunklank, "A Twitter Analog to PageRank" http://thenoisychannel.com/2009/01/13/a-twitter-analog-to-pageran/=