Monitoring Blogosphere S Korea

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

Blog?
Online personal diary
Social media:
Interactive communication
Online community
Communal contents
Expansion of social networks/Diffusion and sharing of information

Political Blog Campaign

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.

Research Objective
This study aims to empirically examine the effectiveness of political blog campaign during the 2009 Korean National Assembly by-election periods.

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)

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

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)

Trend Analysis
Jangan district in Suwon City, Gyeonggi Province
(Park, CS)
(Lee, CY)
(Ahn, DS)
(Yoon, JY)

Trend Analysis
Sangrok-B district in Ansan City, Gyeonggi Province
(Song, JS)
(Kim, YH)
(Jang, KW)
(Kim, SK)
(Yoon, MW)
(Lee, YH)
(Lim, JI)

Trend Analysis
Gangreung district in Gangwon Province
(Kwon, SD)
(Hong, JK)
(Song, YC)
(Shim, KS)

Trend Analysis
Jeungpyeong-Jincheon-Geoisan-Eumsung district in North Chungcheong Province
(Kyoung, DS)
(Chung, BG)
(Chung, WH)
(Park, KS)
(Lee, TH)
(Kim, KH)

Trend Analysis
Yangsan district in South Gyungsang Province
(Park, HT)
(Song, IB)
(Park, SH)
(Kim, SG)
(Kim, YS)
(Kim, YK)
(Kim, JM)
(Yoo, JM)

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)

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)

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)

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)

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)

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)

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.

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.

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.

Thank you for your attention.

Monitoring Blogosphere S Korea

by WCU Webometrics Institute

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