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Webometrics analysis localmedia

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  • 영남 , 매일이 오프라인 온라인 선호도에서 월등하게 두드러짐
  • From scheffe post-hoc test, 이러한 통계적 차이는 영남일보와 매일신문이 타신문사들에 비해 웹사이트 만족도에서 높은 점수를 얻은 것으로부터 비롯되었음을 확인했다 .
  • MBC, KBS, (Major company 의 인지도 덕분에 대구 mbc, 대구 kbs 선호도가 높게 나타난 걸로 추측 ) TBC 두 부분에서 모두 두드러지게 높음
  • 방송사 웹사이트 만족도간에는 통계적으로 유의미한 차이가 있는 것으로 확인됨
  • 큰 차이는 없으나 cmb, gcs 가 대체로 선호도에서 높게 나타남
  • 웹사이트 만족도는 대체로 비슷 , 통계적으로 유의미한 차이가 없음 .
  • 빨간색 : 신문사 노란색 : 지상파 / 라디오 방송국 하늘색 : 케이블 TV 3 clusters: 1) 선호도가 높은 지상파 TV/ 신문사 그룹 2) 케이블 TV 그룹 3) isolated groups: 채널선호도에서 낮은 지지도를 받은 특수 방송사와 대구 MBC ( 관계자의 말에 따르면 웹사이트 관리 잘안함 ..)

Transcript

  • 1. Webometrics Analaysis of Local Media in South Korea : Focused on University students Se Jung Park Ph.D. Student, Georgia State University, USA Han Woo Park Director, Cyber Emotions Research Center Associate Professor, Yeungnam University, South Korea Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 2. Introduction
    • In the smart society, media environment has changed and media companies have utilized the Internet as an alternative channel.
    • How do local media being perceived among residents and do people satisfy their services?
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 3. Research objectives
    • Identifying audience preference, satisfaction of regional media companies in Daegu and Gyeongbuk area
    • Measuring indirect perception of users using social network analysis by discovering the hidden network
    • To provide a comprehensive description of circumstances and online presences of local media in South Korea from audience-oriented approach
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 4. Literature Review
    • -Studies on local media in South Korea
    • Han(2003) In spite of the importance of regional journalism, there is little academic interest and studies on local media, so it is difficult to figure out its social consequences.
    • Kim & Kim(1990) Existed studies examining regional journalism have focused on general remarks. The research topic, methods are too narrow to fully understand local media itself.
    • Seol(2003) Most existed studies have mainly analized major broadcasting companies instead of local media in diverse regions.
    • Ahn, et al.(2006) To reflect the needs of communities and strengthen the competitiveness of local media, the study from an audience approach is necessary,
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 5. Research Questions
    • To what extent do students prefer newspapers in Daegu and
    • Gyeongbuk area?
    • Is there correlation between offline and online preference?
    • To what extent do students satisfy the websites of the newspapers?
    • To what extent do student prefer broadcasting companies in Daegu
    • and Gyeongbuk area?
    • Is there correlation between offline and online preferences?
    • To what extent do student satisfy the websites of the companies?
    • To what extent do student prefer cable television companies in
    • Daegu and Gyeongbuk area?
    • Is there correlation between offline and online preferences?
    • To what extent do student satisfy the websites of the companies?
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 6. Method
    • Online survey
    • Statistics
    • Social Network Analysis
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 7. Online survey
    • - Data collection
    • 174 University students in Gyeongbuk area using convenience sampling
    • Average age of respondents: 26 year old
    • - Measurement
    • Preference: Rank from most to least
    • Website satisfaction: 11 likert scale
    • - Statistics
    • Pearson correlation
    • One-way ANOVA
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 8. Social Network Anlaysis
    • Web o metrics = World Wide Web + Metrics
    • - Co-link analysis
    • To reveal hidden network structure from an aggregation level
    • Collecting co-link data from LexiURL software
    A B C A B Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 9. A list of media companies
    • 6 newspapers
    • 7 broadcasting stations (3TVs/4radios)
    • 8 cable televisions
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 10. Results
    • - Preferences for newspapers
    - Preferences for websites of newspapers Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Daegu Daegu Daily Maeil Yeongnam Daily Weekly Life Palgong 8.9% 3.8% 54.8% 30.6% 0.0% 1.9% Daegu Daegu Daily Maeil Yeongnam Daily Weekly Life Palgong 10.8% 3.6% 49.6% 27.3% 5.8% 2.9% Cyber Emotions Research Center
  • 11. Results
    • - Pearson correlation analysis
    - Spearman correlation analysis N=852, **p<.01 N=6, **p<.01 Offline and online channels are positively correlated Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Offline preference Online preference .721 ** Offline preference Online preference 1.000 ** Cyber Emotions Research Center
  • 12. Results
    • - Website satisfactions of newspapers
    - Results of ANOVA **p<.01 N=157 Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Daegu Daegu Daily Maeil Yeongnam Daily Weekly Life Palgong 5.9 (N=127) 5.8 (N=129) 6.7 (N=127) 6.7 (N=128) 6.0 (N=129) 5.3 (N=127) Sum of Squares df Mean Square F Sig. Between Groups 185.709 5 37.142 10.633 ** .000 Within Groups 2658.205 761 3.493 Total 2843.914 766 Cyber Emotions Research Center
  • 13. Results
    • Preferences for broadcasting station
    • Preferences for websites of broadcasting stations
    • N=118.
    N=150 Presented at 2011 SICSS, Shanghai, 18 Aug 2011 MBC KBS TBC CBS BBS PBC TBN 56.0% 11.3% 24.7% 2.7% 0.7% 0.7% 4.0% MBC KBS TBC CBS BBS PBC TBN 55.9% 13.6% 20.3% 5.9% 1.7% 0.8% 1.7% Cyber Emotions Research Center
  • 14. Results
    • -Pearson correlation analysis
    • N=854, **p<.01
    • - Spearman correlation analysis
    • N=7, **p<.01
    • Offline and online channels are positively correlated
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Offline preference Online preference .754 ** Offline preference Online preference .964 ** Cyber Emotions Research Center
  • 15. Results
    • - Website satisfactions of broadcasting stations
    - Results of ANOVA **p<.01 Presented at 2011 SICSS, Shanghai, 18 Aug 2011 MBC TBC KBS TBN CBS BBS PBC 7.2 (N=114) 6.9 (N=114) 6.9 (N=114) 6.3 (N=115) 6.1 (N=112) 5.5 (N=114) 5.4 (N=113) Sum of Squares df Mean Square F Sig. Between Groups 354.218 6 59.036 17.321 ** .000 Within Groups 2699.399 792 3.408 Total 3053.617 798 Cyber Emotions Research Center
  • 16. Results
    • - Preferences for cable televisions
    • N=139
    - Preferences for websites of cable televisions N=109 Presented at 2011 SICSS, Shanghai, 18 Aug 2011 CMB GCS Qrix SCS SDTV TCN1 TCN2 HCN 15.8% 20.9% 4.3% 5.0% 15.1% 14.4% 14.4% 10.1% CMB GCS Qrix SCS SDTV TCN1 TCN2 HCN 23.9% 11.9% 6.4% 10.1% 17.4% 11.9% 10.1% 8.3% Cyber Emotions Research Center
  • 17. Results
    • - Pearson correlation analysis
    N=912, **p<.01 - Spearman correlation analysis N=8, **p<.01 Offline and online channels are positively correlated Presented at 2011 SICSS, Shanghai, 18 Aug 2011 offline preference online preference .579 ** offline preference online preference .905 ** Cyber Emotions Research Center
  • 18. Results
    • -Website satisfactions of cable televisions
    - Results of ANOVA Presented at 2011 SICSS, Shanghai, 18 Aug 2011 CMB GCS Qrix SCS SDTV TCN1 TCN2 HCN 6.2 (N=104) 6.3 (N=104) 6.2 (N=102) 6.2 (N=103) 6.5 (N=102) 6.3 (N=103) 6.4 (N=103) 5.9 (N=100) Sum of Squares df Mean Square F Sig. Between Groups 25.310 7 3.616 1.226 .285 Within Groups 2397.374 813 2.949 Total 2422.685 820 Cyber Emotions Research Center
  • 19. Results
    • - Social Network Map of Local Media in Daegu and Gyeongbuk area
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 20. Conclusion & Discussion
    • This study would help comprehensive understanding audience perceptions of local media using mixed methods (online survey, SNS) for both offline and online channels.
    • It could provide practical implications to judge to what extend certain local medium utilizes online resource efficiently and give material to make a policy to develop the website of the medium as an alternative news channel.
    • This study shows how to apply Webometrics analysis to examine various types of journalism. Especially, co-link analysis would visualize hidden structural relationships among specific media platforms using huge online data generated by users which was not possible with traditional research methods.
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center
  • 21.
    • Thank you!
    • [email_address]
    • [email_address]
    • http://www.slideshare.net/hanpark
    Presented at 2011 SICSS, Shanghai, 18 Aug 2011 Cyber Emotions Research Center