tracking web visibility of korean politicians
TRANSCRIPT
WEBOMETRICSINSTITUTE
Tracking web visibility of Korean politicians:
How and why congressional members appear on the web?
Yon Soo Lim, Han Woo Park, & Ting Wang WCU Webometrics Institutute
Yeungnam UniversityE-mail: [email protected]
Introduction Internet as social media:
Interactive communication Expansion of social networks Diffusion and sharing of information
Online political campaigning is expected to promote close relationship between politicians and citizen. Draw citizen’s attention to politicians or political
events. Mobilize citizen’s support and political engage-
ment.
Introduction Previous studies on Internet politics have tried
to identify the effectiveness of online cam-paigning.
However, most studies have overlooked the existing political aspect of Internet media it-self.
Specifically, it is unclear who is currently the center of public attention on the web, and why the political actor is the dominant posi-tion on the web.
Research Objective This study aims to identify the existing aspect
of Korean political webosphere by tracking who is the most visible politicians on the web and investigating why the politicians is more visible than others.
Specifically, it focused on the web visibility of the 18th National Assembly members in South Korea and their socio-demographic attributes.
Web Visibility Web visibility
Presence or appearance of actors or issues being discussed by the public (Internet users) on the web.
Tracking web visibility is powerful way to get an insight into public reactions to actors or issues.
The limitations of previous web visibility re-search Focus on academic or business contexts rather
than politics. Lack of the studies on the relationship between
web visibility and inherent attributes from offline world.
Lack of the studies on non-English based webo-sphere.
Theoretical argument Political role of the Internet
Normalization perspective: Internet may reflect the traditional power struc-ture among individual politicians.
Equalization (Innovation) perspective: Internet may reform the offline hierarchical struc-ture of individual politicians.
This study argues that the political effect of the Internet cannot be easily classified into one of the two models. Therefore, it does not take any particular position.
Research Questions
Who are the most visible congressional mem-
bers on Korean webosphere?
Are web visibilities of individual congressional
members are different by their socio-demo-
graphic attributes?
Method Data
Subject: 18th Korean National Assembly members elected in
April 2008. 285 of 292 members were examined. 7 members with irrelevant data were excluded.
Politicians’ attribute data Demographic attributes: gender & age Political attributes: parliament term, constituency, &
party affiliation Gathered from National Assembly’s official site (http://
www.assembly.go.kr) and the politicians’ homepages.
Socio-demographic information of 285 National Assembly Members in South Korea 1
Category Count % 2
Gender Female 41 14.4% 3
Male 244 85.6% 4
Age under 50 53 18.6% 5
50-54 74 26.0% 6
55-59 66 23.2% 7
60-64 48 16.8% 8
over 64 44 15.4% 9
Term First-term 125 43.9% 10
Second-term 87 30.5% 11
Third-term and more 73 25.6% 12
Constituency Provincial region 129 45.3% 13
National Capital region 105 36.8% 14
Proportional representation 51 17.9% 15
Party Affiliation Opposition Party 122 42.8% 16
Ruling Party 163 57.2% 17
18
Method
Method Data gathering for measuring web visibility
A popular Korean-language based search engine, Naver.com
WeboNaver, an API-based program by WWI Search query:
The name of the politicians + “의원 : National Assembly member”
Collected across different web platforms including blog, image, news, and website.
Search date: Dec. 30, 2009
Analysis Descriptive statistics
Identify the rank order of politicians’ web visibility
Correlation analysis (Pearson & Spearman) Identify the relationships among the four types of
web visibility indices (blog, news, image, & web-site)
Median test, Kruskal-Wallis test, & Mann-Whit-ney U test Identify the relationships between politicians’ at-
tributes and the levels of web visibility
ResultsDescriptive statistics of web visibility indices 1
Blog Image News Web 2
N 285 285 285 285 3
Mean 3,122.47 101.50 6,269.79 77,633.01 4
Median 2,051 54 3,734 48,065 5
SD 4,615.38 147.09 9,004.27 108,892.52 6
Skewness 7.30 3.71 5.48 6.11 7
Kurtosis 74.45 16.99 43.01 54.62 8
Minimum 380 7 395 3,519 9
Maximum 57,915 1,152 97,514 1,272,654 10
11
ResultsCorrelation among web visibility indices 1
1 2 3 4 2
1. Blog r - .822** .963** .934** 3
rho - .867** .955** .814** 4
2. Image r - .838** .783** 5
rho - .864** .734** 6
3. News r - .912** 7
rho - .773** 8
4. Web r - 9
rho - 10
Note. N = 285, **p < .01 (two-tailed test). 11
Results Factor analysis for web visibility indices
Correlations among four indices: greater than .50 (p < .01)
Kaiser-Meyer-Olkin (.85) Bartlett’s test (χ2 = 1665.84, df = 6, p < .01) One factor: 90.73% of the variance Factor score coefficients:
blog .27; image .25; news .27; web site .26 With these factor weights, web visibility of each
politician was calculated (M = 22,969.17; SD = 32,065.53).
ResultsList of top 10 in overall web visibility
Visibility Gender Age Term Constituency Party
Top 10
1 Geun-hye Park 376,804.10 Female 58 4 Provincial Ruling
2 Sye-kyun Chung 166,961.02 Male 60 4 Provincial Opposition
3 Hoi Chang Lee 165,114.46 Male 75 3 Provincial Opposition
4 Mong Joon Chung 156,551.21 Male 59 6 Capital Ruling
5 Dong Young Chung 137,064.78 Male 57 3 Provincial Opposition
6 Hyoung O Kim 112,590.96 Male 63 5 Provincial Opposition
7 Sang Soo Ahn 112,506.43 Male 64 4 Capital Ruling
8 Joon Pyo Hong 107,661.65 Male 56 4 Capital Ruling
9 Ki Kab Kang 103,486.98 Male 57 2 Provincial Opposition
10 Kyung Won Na 88,185.61 Female 47 2 Capital Ruling
ResultsList of bottom 10 in overall web visibility
Visibility Gender Age Term Constituency Party
Bottom 10
1 Doo Ah Lee 1,155.45 Female 39 1 Proportional Ruling
2 Kum Lae Kim 2,354.61 Female 58 1 Proportional Ruling
3 Young Hee Jung 2,733.34 Female 65 1 Proportional Opposition
4 Ok Lee Kim 2,814.14 Female 63 1 Proportional Ruling
5 Jin Sam Lee 3,254.55 Male 73 1 Provincial Opposition
6 Choon Sik Lee 3,396.38 Male 61 1 Proportional Ruling
7 Yong Sam Lee 3,497.13 Male 53 4 Provincial Opposition
8 So Nam Kim 3,773.46 Female 61 1 Proportional Ruling
9 Gyu Back Ahn 3,921.04 Male 49 1 Proportional Opposition
10 Jae Jung Yoo 3,932.65 Male 54 1 Provincial Ruling
Results
Results of the median test and the Kruskal-Wallis test for gender difference 1
Gender Frequency Mean Median test Kruskall-Wallis 2
N >M* <=M* rank χ 2 p χ 2 p 3
Blog Female 41 19 22 127.98 0.232 0.630 1.591 0.207 4
Male 244 123 121 145.52 5
Image Female 41 20 21 134.50 0.009 0.924 0.509 0.475 6
Male 244 121 123 144.43 7
News Female 41 19 22 125.27 0.232 0.630 2.217 0.137 8
Male 244 123 121 145.98 9
Web Female 41 16 25 123.61 2.234 0.135 2.651 0.103 10
Male 244 126 118 146.26 11
Note. M* = Median 12
ResultsResults of the median test and the Kruskal-Wallis test for age difference 1
Age Frequency Mean Median test Kruskall-Wallis 2
N >M* <=M* rank χ 2 p χ 2 p 3
Blog under 50 53 21 32 136.04 4
50-54 74 39 35 145.36 5
55-59 66 35 31 148.60 2.822 0.588 0.805 0.938 6
60-64 48 25 23 141.98 7
over 64 44 22 22 140.13 8
Image under 50 53 23 30 136.97 9
50-54 74 39 35 147.84 10
55-59 66 35 31 149.70 1.526 0.822 1.439 0.837 11
60-64 48 23 25 140.28 12
over 64 44 21 23 135.03 13
News under 50 53 19 34 129.97 14
50-54 74 37 37 141.58 15
55-59 66 36 30 149.53 5.628 0.229 1.988 0.738 16
60-64 48 27 21 145.98 17
over 64 44 23 21 148.03 18
Web under 50 53 24 29 131.81 19
50-54 74 39 35 143.90 20
55-59 66 34 32 154.14 1.897 0.755 3.207 0.524 21
60-64 48 26 22 148.74 22
over 64 44 19 25 132.00 23
Note. M* = Median 24
ResultsResults of the median test and the Kruskal-Wallis test regarding consecutive term 1
Term Frequency Mean Median test Kruskall-Wallis 2
N >M* <=M* rank χ 2 p χ 2 p 3
Blog First 130 19 111 83.65 4
Second 89 66 23 186.73 118.773 0.000 132.691 0.000 5
More** 73 61 12 209.37 6
Image First 130 25 105 92.53 7
Second 89 63 26 180.37 85.41 0.000 98.196 0.000 8
More** 73 56 17 201.32 9
News First 130 13 117 76.62 10
Second 89 69 20 189.20 151.62 0.000 165.473 0.000 11
More** 73 64 9 218.90 12
Web First 130 36 94 101.88 13
Second 89 59 30 175.60 46.847 0.000 66.666 0.000 14
More** 73 51 22 190.48 15
Note. M* = Median; More** = Third-term and more 16
ResultsResults of the median test and the Kruskal-Wallis test regarding constituency 1
Constituency Frequency Mean Median test Kruskall-Wallis 2
N >M* <=M* rank χ 2 p χ 2 p 3
Blog Provincial 129 74 55 152.18 4
Capital 105 56 49 159.82 17.556 0.000 31.094 0.000 5
Proportional 51 12 39 85.16 6
Image Provincial 129 67 62 146.57 7
Capital 105 59 46 159.00 10.420 0.005 17.421 0.000 8
Proportional 51 15 36 101.04 9
News Provincial 129 77 52 157.80 10
Capital 105 54 51 153.59 21.418 0.000 32.238 0.000 11
Proportional 51 11 40 83.76 12
Web Provincial 129 67 62 156.24 13
Capital 105 61 44 151.25 13.315 0.001 23.506 0.000 14
Proportional 51 14 37 92.53 15
Note. M* = Median 16
Results
Results of the median test and the Kruskal-Wallis test regarding party affiliation 1
Party Frequency Mean Median test Kruskall-Wallis 2
N >M* <=M* rank χ 2 p χ 2 p 3
Blog Opposition 122 73 49 157.70 8.552 0.003 6.787 0.009 4
Ruling 163 69 94 132.00 5
Image Opposition 122 72 50 161.10 7.771 0.005 10.293 0.001 6
Ruling 163 69 94 129.45 7
News Opposition 122 75 47 162.78 11.582 0.001 12.285 0.000 8
Ruling 163 67 96 128.20 9
Web Opposition 122 68 54 161.18 2.983 0.084 10.380 0.001 10
Ruling 163 74 89 129.39 11
Note. M* = Median 12
Discussion This study measured the web visibility of
South Korean National Assembly members us-ing an API-based Naver search tool.
Also, it systematically examined the relation-ships between the levels of the web visibility and the socio-demographic attributes of the congressional members.
Discussion RQ1. Who are the most visible congressional
members in the Korean webosphere? The top 10 members are very popular politicians in
Korea. Geun-hye Park: 1) the chairperson of the Grand National
Party from 2004 to 2006, 2)the fourth consecutive term, 3) a recent public opinion poll conducted by Korean Her-ald Business newspaper reported that Geun-hye Park is the most influential politician in South Korea (Shin, 2009, October 5).
The bottom 10 members have relatively lower popu-larity. Newly elected members, proportional representation,
elected from sparsely populated region.
Discussion RQ2. Are web visibilities of individual con-
gressional members are different by their socio-demographic attributes?
Demographic attributes, such as gender and age, are not significantly associated with the levels of the web visibility.
However, political attributes, such as parliament term, constituency, and party affiliation, were sig-nificantly related. Term: 3rd term and more > 2nd term > 1st term Constituency: provincial regions = national capital re-
gions > proportional representation Opposition party members > ruling party members
Discussion Normalization vs. Equalization Normalization perspective
The most visible politicians in the Korean webosphere have a highly qualified political career and eminence.
Their levels of the web visibility seem to reflect their off-line power.
Equalization perspective The web visibility ranks of the ruling party members who
are an absolute majority in the National Assembly were significantly lower than those of the opposition party members.
The results seem to indicate the equalization effect that the Internet will play a major role in changing traditional political hierarchy.
Discussion However, the difference of the web visibility levels
between the ruling party members and the opposi-tion party members can be caused from a political career factor.
Thus, the difference in the party affiliation can be based on the offline power structure of individual politicians. At this point, the normalization ap-proach may be better than the equalization ap-proach to explain the party difference.
Cross table between party affiliation and parillament term 1
First-term Second-term Third & more Total 2
Opposition Parties 41 (33.6%) 47 (38.5%) 34 (27.9%) 122 (100%) 3
Ruling Party 84 (51.5%) 40 (24.5%) 39 (23.9%) 163 (100%) 4
Discussion Overall, these findings suggest that the politi-
cians who have political power and influence, based on their political career, in the offline world are more visible on the web.
It is likely that the traditional power structure is transferred to the online world.
While this study demonstrates a limitation of the equalization effect that the Internet will re-form the offline hierarchical structure of indi-vidual politicians, it supports the normaliza-tion argument that the Internet is a replication of the real world.
Limitations and Future Studies Future studies should consider more compre-
hensive variables that can indicate the politi-cians’ inherent advantages in the offline world. (e.g. politician’s activities or their fi-nancial donations)
Future studies should provide a more detailed understanding of web visibility by considering the change over time.
Future studies should develop a mixed ap-proach between qualitative and quantitative on the web visibility measure.
Implication & Conclusion This study as a case study of South Korea iden-
tified a significant relationship between web visibility and politicians’ inherent attributes.
The findings suggests that Korean webosphere is more likely to reflect and reproduce existing political power structure of individual politi-cians.
Also, this study provides us with ubiquitous presence in digitalized society.
