Browse > Article
http://dx.doi.org/10.5392/JKCA.2016.16.09.751

The Effect of Information Diffusion of Program on the Viewing Type of Web Platform Program and the Attention of the Public  

Hong, Juhyun (국민대학교 언론정보학부)
Publication Information
The Journal of the Korea Contents Association / v.16, no.9, 2016 , pp. 751-768 More about this Journal
Abstract
The success of the journey to the west of tvN's shows the positive prospect of web entertainment. This study highlights how viewers actively select web progrmas and how they diffuse the infomrmation of web programs to explore the possibility of success of web program and the change of viewing environment. This study revealed the attention of viewers affected the diffusion of programs via social media. The highness of the viewer's attention cause the highness of active interaction between users. The production company of web entertaninment has to focus on the high hits strategy. In the view of journalists, they covered on the appearance of the heroin rather than the content of the program. The relationship of viewing type and viral type via SNS is related with the activity of viewers. If viewers participate in viewing they express their opinion on the web entertainment actively.
Keywords
Web Platform; Web Program; The Attention of the Public; Issue Diffusion; Social Media;
Citations & Related Records
연도 인용수 순위
  • Reference
1 국내외 모바일 동영상 콘텐츠 이용 행태, 한국콘텐츠진흥원 참조.
2 '99% of Consumers Multitask While Watching TV' https://www.exchangewire.com/blog/2015/11/12/
3 http://www.viva100.com/main/
4 Y. C. Pick, Mobile strategies in political communication. In Partial Fulfillment of the Requirement for the Degree of Master of Arts in Public Communication, 2010. http: www.american.edu/soc/communication/upload
5 J. Torez-Relly, The Social TV Phenomenon:New Technologies Look to Enhance Television's Role as an Enabler of Social Interaction. 2011. http://www.torrezriley.com/projects/researchpaper/SocialTVpaper.pdf
6 B. S. Adam and G. Gips, "Media Multitasking Behavior: Concurrent Television and Computer Usage," Cyberpsuchology, Behavior and Social Networking, Vol.14, No.9, pp.527-534, 2011. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171998/   DOI
7 S. D. Park, "Social TV: A new wave of Social Networking for Television. https://www.w3.org/2008/09/msnws/papers/Samsung-PositionPaper.pdf
8 G. Alberto, Roles of audience participation in multiplatform television: From fans and consumers, to collaborators and activists," 2012.
9 TV드라마 '미생'이 웹드라마를 살렸다? 한국일보, http://www.hankookilbo.com/v/bb2e0d.
10 J. Yang and J. Leskivec, Modeling Information Diffusion in Implicit Networks, 2011.
11 P. David and D. Moran, The Economic Value Of Bioversity, Earthscan Publications Ltd, London. Available at: https://www.cbd.int/doc/external/iucn/iucn-biodiversity-value-1994-en.pdf
12 S. C. Zyglidopoulos and A. P. Georgiadis, Media Visibility as a Driver of Corporate Social Performance, Working Paper Series, Judge Business School, University of Cambridge. This paper was presented at the 2nd International Conference on Corporate Responsibility in Berlin, Germany, 12-13 October 2006. Available at : https://www.jbs.cam.ac.uk/fileadmin/user_upload/research/workingpapers/wp0616.pdf
13 P. A. Glore and Y. Zhao, Analyzing Actors and Their Discussion Topics by Semantic Social Network Analysis.Information Visualization, 2006. IV 2006. Tenth International Conference on Date of Conference: 5-7, pp.130-135, July. 2006.
14 D. A. Graber and J. Dunaway, Mass Media and American Politics. CQ PRESS:A Division of SAGE Washington, D.C. 2015.
15 P. Shoemaker and S. Reese, Mediating the Message: Theories of Influences on Mass Media Content, Allyn & Bacon, 1995.
16 G. Alberto, Roles of audience participation in multiplatform television: From fans and consumers, to collaborators and activists, 2012.
17 홍주현, 윤해진, "18대 대통령 선거 후보자의 연설문 네트워크 분석 : 단어의 가시성(visibility)과 단어 간 연결성(connectivity)을 중심으로," 한국콘텐츠학회논문지, 제9권, pp.24-44, 2009.
18 Author's own research 분류체계 참조 (Garcia-Aviles, 2012).
19 B. Pang and L. Lee, Opinion mining and sentiment analysis. and Trends in Information Retrieval, 2(1-2), 1-135, 2008. Available at: http://www.cs.cornell.edu/home/ llee/omsa/omsa.pdf
20 J. Yang and J. Leskivec, Modeling Information Diffusion in Implicit Networks, 2010.
21 Diakopolous A. Nicholas and D. A. Shamma, Characterizing debate performance via aggregated twitter sentiment. In Conference on Human Factors in Computing Systems(CHI), April, 2010. research.yahoo.com/files/note0655-diakopoulos.pdf