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Monitoring Blogosphere S Korea

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  • 1. Monitoring a Socio-political Blogosphere in South Korea
    Comparing a Metrics from Blogosphere with Voter Turnout
    Yon Soo Lim & Han Woo Park
    WCU WebometricsInstitutute
    Yeungnam University
    E-mail: yonsoolim@gmail.com
  • 2. Blog?
    Online personal diary
    Social media:
    Interactive communication
    Online community
    Communal contents
    Expansion of social networks/Diffusion and sharing of information
  • 3. Political Blog Campaign
  • 4. Political Blog Campaign
    International studies on political blog campaign
    2004U.S. presidential election (Blog for America)
    Anstead & Chadwick, 2008; Drezner & Farrell, 2008; Kerbel & Bloom, 2005; Trammell, 2006; Trammell et al., 2006
    2005U.K. general election
    Coleman & Ward, 2005; Jackson, 2007; Stanyer, 2006
    2005New Zealand general election
    Hopkins & Matheson, 2005
    2005Danish parliamentary election
    Klastrup & Pedersen, 2007
    2005German bundestag election
    Albrecht, Lübcke, & Hartig-Perschke, 2007
    2007Australian federal election
    Kirchhoff, Nicolai, Bruns, & Highfield, 2009
    2008presidential and congressional election
    Metaxas & Mustafaraj, 2009; Smith, 2009
    However, the blogosphere research on Korean political elections has been rarely conducted.
  • 5. Research Objective
    This study aims to empirically examine the effectiveness of political blog campaign during the 2009 Korean National Assembly by-election periods.
  • 6. Method
    Data
    Blog postings related to 29 candidates for the 2009 Korean National Assembly by-election.
    Data gathering
    Korean-language based blog search engine by Naver.com
    Real-time blog monitoring program by WWI
    Search queries:the name of candidate+“candidate”
    Search date:After Oct. 8, 2009
    Data collection periods:Oct. 16 – Oct. 27, 2009 (12 days)
    Cycle:Twice per a day (AM 00:00, PM 12:00)
  • 7. Analysis
    Trend analysis
    Tracing change over time
    Correlation analysis (Pearson & Spearman)
    Regarding 29 candidacies, the average number of blogs per candidate & the number of votes
    Simple regression analysis
    I.V.: the average number of blogs in each candidate
    D.V.: the number of votes
  • 8. Descriptive Information
    Real-time blog monitoring: total 20 times
    Cumulative number of blogs:total62,672
    The average number of blogs:108.06(SD=81.96, N=29)
    Highest:Kim, YW (M=280.1)
    Lowest:Yoon, JY (M=11.8)
  • 9. Trend Analysis
    Jangan district in Suwon City, Gyeonggi Province
    (Park, CS)
    (Lee, CY)
    (Ahn, DS)
    (Yoon, JY)
  • 10. Trend Analysis
    Sangrok-B district in Ansan City, Gyeonggi Province
    (Song, JS)
    (Kim, YH)
    (Jang, KW)
    (Kim, SK)
    (Yoon, MW)
    (Lee, YH)
    (Lim, JI)
  • 11. Trend Analysis
    Gangreung district in Gangwon Province
    (Kwon, SD)
    (Hong, JK)
    (Song, YC)
    (Shim, KS)
  • 12. Trend Analysis
    Jeungpyeong-Jincheon-Geoisan-Eumsung district in North Chungcheong Province
    (Kyoung, DS)
    (Chung, BG)
    (Chung, WH)
    (Park, KS)
    (Lee, TH)
    (Kim, KH)
  • 13. Trend Analysis
    Yangsan district in South Gyungsang Province
    (Park, HT)
    (Song, IB)
    (Park, SH)
    (Kim, SG)
    (Kim, YS)
    (Kim, YK)
    (Kim, JM)
    (Yoo, JM)
  • 14. Blogs vs. Votes
    Jangan district in Suwon City, Gyeonggi Province
    N. of Votes
    N. of Blogs
    (Park, CS)
    (Lee, CY)
    (Ahn, DS)
    (Yoon, JY)
    (Park, CS)
    (Lee, CY)
    (Ahn, DS)
    (Yoon, JY)
  • 15. Sangrok-B district in Ansan City, Gyeonggi Province
    Blogs vs. Votes
    N. of Votes
    N. of Blogs
    (Jang, KW)
    (Song, JS)
    (Kim, YH)
    (Kim, SK)
    (Yoon, MW)
    (Lee, YH)
    (Lim, JI)
    (Jang, KW)
    (Song, JS)
    (Kim, YH)
    (Kim, SK)
    (Yoon, MW)
    (Lee, YH)
    (Lim, JI)
  • 16. Blogs vs. Votes
    Gangreung district in Gangwon Province
    N. of Votes
    N. of Blogs
    (Kwon, SD)
    (Hong, JK)
    (Song, YC)
    (Shim, KS)
    (Kwon, SD)
    (Hong, JK)
    (Song, YC)
    (Shim, KS)
  • 17. Blogs vs. Votes
    Jeungpyeong-Jincheon-Geoisan-Eumsung district in North Chungcheong Province
    N. of Votes
    N. of Blogs
    (Kyoung, DS)
    (Chung, BG)
    (Chung, WH)
    (Park, KS)
    (Lee, TH)
    (Kim, KH)
    (Kyoung, DS)
    (Chung, BG)
    (Chung, WH)
    (Park, KS)
    (Lee, TH)
    (Kim, KH)
  • 18. Blogs vs. Votes
    Yangsan district in South Gyungsang Province
    N. of Votes
    N. of Blogs
    (Park, HT)
    (Song, IB)
    (Park, SH)
    (Kim, SG)
    (Kim, YS)
    (Kim, YK)
    (Kim, JM)
    (Yoo, JM)
    (Park, HT)
    (Song, IB)
    (Park, SH)
    (Kim, SG)
    (Kim, YS)
    (Kim, YK)
    (Kim, JM)
    (Yoo, JM)
  • 19. Results
    Correlation Analysis (N. of Blogs &N. of Votes)
    Pearson r = .586, p < .01 (N=29)
    Spearman rho = .797, p < .01 (N=29)
    Simple Regression Analysis
    N. of Votes =1,055.56+79.99(N. of Blogs)
    R2 = .344 (F = 14.128, p < .01)
    ß=.586(t = 3.759, p < .01)
  • 20. Summary
    Overall, the number of blogs by candidates has a tendency to increase over time.
    By districts, the candidate who has the largest blog postings won the election.
    The results of correlation analyses (Pearson and Spearman) significantly indicate the positive relationship between blog postings and votes.
    From the results of a simple regression analysis, the number of blogs by candidatescan be regarded as a significant determinant of the number of votes.
  • 21. Future Research
    Consider the qualitative approaches for blog contents.
    Develop a more sophisticated model for prediction and analysis, considering various variables (socio-demographic and off-line campaign activities).
    Require advanced e-research tools for data collection and analysis of massive blogosphere.
  • 22. Implication
    This study empirically investigated the effectiveness of political blog campaign, based on a case study of South Korea.
    Real-time online monitoring can be applied for tracing and analyzing various socio-political issues.
    This study suggests a possibility for predictive modeling related to blog marketing.
  • 23. Thank you for your attention.

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