Virtual Knowledge Studio (VKS)
Political hyperlinks in
Web 1.0 and Web 2.0
Dr. Han Woo PARK
Visiting Research Fellow
Oxford Internet Institute, UK
Associate Professor
Department of Media & Communication
YeungNam University
214-1 Dae-dong, Gyeongsan-si, Gyeongsangbuk-do 712-749
Republic of Korea
hanpark@ynu.ac.kr
http://www.hanpark.net
A co-leader of WCU Project:
Investigating Internet-based Politics with e-Research Tools.
Invited speech, Statistical Cybermetrics Research Group, University of Wolverhampton, UK, 27 May, 2009
1

Three topics for today
• Is a hyper-linking socio-political or
technical behavior?
• How different/similar are hyper-linking
practices between Web 1.0 and Web
2.0?
• What are advantages of massively-
collected hyper-link data using search
engines for political and electoral
communication research?
2

A comment from those who are
NOT doing a link analysis
• In a chapter of The Sage Handbook of
Online Research Methods edited by
Fielding et al. (2008), Horgan emphasizes
that „link analysis‟ has become an active
research domain in examining social
behavior online.
3

http://participatorysociety.org/wiki/index
.php?title=Online_Research

Part 1
This part is based on
• Kim, H., & Park, H. W. (2007). Web sphere analysis for political
websites: The 2004 national assembly election in South Korea. In
Kluver, R., Jankowski, N., Foot, K., & Schneider, S. (Eds.). The
internet and national elections: A comparative study of web
campaigning. London: Routledge. pp. 226-239.
• Park, H. W., & Kluver, R. (2008). Affiliation in political blogs in South
Korea: Comparing online and offline social networks. In Goggin, G.,
& McLelland, M. (Eds.). Internationalizing Internet Studies. London:
Routledge. pp.252-263.
5

How political are hyperlinks?
• Social roles of hyperlinks in Internet-
mediated political communication (Foot &
Schneider, 2006, Web campaigning)
• Informing
• Involving
• Connecting
• Mobilizing
6

Link to central government (66 out of 77 links
to Blue-House came from ruling party members)
7

Connecting: Endorsement
8

Connecting: Endorsement
9

Mobilizing: Send a link to local friends who can vote
10

Mobilizing: Send a link telling that this is a good homepage
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Mobilizing: Send a link sharing emotional support
12

South Korean and Japanese political
cultures: Same? Different?
Relationships South Korea Japan
Party-politician  Weak  Weak/strong (major/
 Leader has strong minor parties)
influence on party  Mediated leader role
Political parties-  Ideologically  Ruling-opposition
public oriented (recently)  Emerging two-party
 Two-party system system
Politicians-public  Increasingly  Increasingly
transparent transparent
 Strong civil society  Weak civil society
 Local support
Election regulations  Strict (media,  Strict (media, timing,
donations, and F2F) and distribution)
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Results (3a): Linking
Linking strategies South Korean Japanese
politicians (N=100) politicians (N=100)
Own political party 89* 70*
Other political parties 4 4
Other politicians in the same party 3* 18*
(national level)
Other politicians in the same party (local 0* 12*
level)
Other politicians in a different party 0 0
(national level)
Other politicians in a different party 0 0
(national level)
Central government 52 38
Local governments 60 44
Local assemblies 8 3
Election-related government bodies 11 3
National assemblies 67* 37*
Parliamentary committees 11 4 14
* = sig. p<0.01

Results (3b): Linking
Linking strategies South Korean politicians Japanese politicians
(N=100) (N=100)
Broadcasters 3 6
Internet broadcasters 0* 27*
Newspapers 9 7
Internet newspapers 9 1
Civic & advocacy 37 23
groups
Wireless sites 2* 15*
Blogs 57* 20*
International bodies 4 7
General public 3* 20*
Other 43 28
15
* = sig. p<0.01

Part 2
This part has been newly prepared for this presentation
using the data of the following publications:
Park, H. W., Kim, C. S., & Barnett, G. A. (2004). Socio-communicational
structure among political actors on the web in South Korea: The dynamics of
digital presence in cyberspace, New Media & Society. 6(3), 403-423
Park, H. W., & Kluver, R. (2009 forthcoming). Trends in online networking among
South Korean politicians-A mixed method approach. Government Information
Quarterly.
* Regarding the National Assembly of South Korea, refer to Wikipedia‟s
entry
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Data collection for Web 1.0
• Official homepages of S. Korean MPs
• Manual collection: Observation
• Inter-linkage: Who links to whom matrix
• Explicit links excluding links in board
• 2-Year tracking of same MPs: 2000-2001
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Web Year Sum Densit Centraliza
types of y tion
links (%)
(Mean) In Out
Web 2000 373 0.006 1.84 69.33
1.0 N=245 (1.52)
Home 2001 515 0.009 1.19 99.55
page (2.10)
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Network map of 2000
Blue: GNP: Conservative: Opposition
Red: MDP: Liberal: Ruling
19

Network map of 2001
Star networks without any isolation 20

Data modification
• Network metrics and diagrams can be heavily
influenced by outliers
- 김홍신(Kim) Outdegree: 170 in 2000-2001
- 박원홍(Park) Outdegree: 0 -> 244 (Outlier?)
- 한승수(Han) Outdegree: 0 -> 99 (Outlier?)
• Free to link, and they may not be outlier
• Their sites might have been refurbished to
increase SEO(Search Engine Optimization)
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Web Year Sum Densit Centraliza
types of y tion
links (%)
(Mean) In Out
Web 2000 373 0.006 1.84 69.33
1.0 N=245 (1.52)
Home 2001 267 0.002 1.20 69.67
page N=243 (1.10)
22

Network map of 2001
before VS after modification
23

2000 VS 2001
(after modification)
Blue: GNP: Conservative: Opposition
Red: MDP: Liberal: Ruling
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Data collection for Web 2.0
• Personal blogs of S. Korean MPs
• Manual collection: Observation
• Blogroll links: Excluding links in postings
• Inter-linkage: Who links to whom matrix
• 2-Year tracking of same MPs: 2005-2006
• Phone interview about usage behaviors
25

Web Year Sum Density Centraliza
types of tion
links (%)
(Mean)
In Out
Web 2005 652 0.067 22.07 41.66
2.0 N=99 (6.59)
Blog
2006 589 0.061 20.67 35.10
(5.95)
26

2005 VS 2006
Blue: GNP: Conservative: Opposition
Yellow: Uri: Liberal: Ruling
Green: DLP: Progressive: Opposition
27

Six-degree on blog?
• Mean and density values indicate that
politicians have about 6 friends on
blogrolls
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Web Year Sum of Density Centralization Note
types links (%)
(Mean)
In Out
Web 1.0 2000 373 0.006 1.84 69.33 Hub but,
(Home N=245 (1.52) overall,
page) sparse
network
2001 515 0.009 1.19 99.55
(2.10)
Web 2.0 2005 652 0.067 22.07 41.66 Disappe
(Blog) N=99 (6.59) aring
hub but
getting
2006 589 0.061 20.67 35.10
denser
(5.95)
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Types Year Gini Characteristics
Web 2000 0.984 Sparse knitted
1.0 N=245 Hub-spike network
(Home Winner-take-all
page) 2001 0.996 Navigation-ability
Website interface
Web 2005 0.759 Fairly connected
2.0 N=99 Buffer-fly network
(Blog) Participatory
2006 0.763 Homophily-based
Personal-tie interface
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To what degree do Korean National
Assembly members update a blog?
Measurement item Answer Frequency Percent
Content-creating Rarely 5 11.4
Activities Occasionally 6 13.6
About half 16 36.4
Frequently 5 11.4
Very Frequently 12 27.3
Hyperlinking Rarely 2 4.5
activities Occasionally 4 9.1
About half 13 29.5
Frequently 7 15.9
Very Frequently 18 40.9
No answer 3 6.
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Part 3
This part is based on
Park, H. W. and Lee, Y. (2008). The Korean Presidential Election of 2007: Five
Years on from the “Internet Election”. Journal of Contemporary Eastern Asia. 7
(1), 1-4.
Lee, Y.-O., & Park, H. W. (2010 forthcoming). The Reconfiguration of E-
Campaign Practices in Korea: A Case Study of The Presidential Primaries of
2007. International Sociology.
Park, H. W. (2009, work-in-progress). How do social scientists use link data
from search engines to understand Internet-based political and electoral
communication.
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Background & Data collection
• The Internet represents a massive
storehouse of social networking data,
enabling researchers to capture political
communications by individual officials,
politicians, and activists.
• This is particularly true in South Korea, where
political participants almost always have
online representation.
• Hyper-linking maps are indicative of the
relative level of public awareness and the
ideological orientation of candidates and
parties.
33

The 2007 presidential race within
the opposition Grand National Party
• Profiles of candidates
– Two major candidates:
Myung-Bak Lee and Geun-
Hye Park
• MB Lee is ex-mayor of Seoul
and ex-CEO of Hyundai
• GH Park is a daughter of ex-
president Jeong-Hee Park
– Two minor candidates but
the two major candidates
were selected for this
research

Difference between public opinion survey
and actual turnout in GNP primary
• Contrary to public opinion
survey, Park ran neck-and-
neck with Lee
– Lee defeated Park only by
1.5% point (2,452 votes)
– Furthermore, Park obtained
423 votes more than Lee
from delegates, party
members, and invited non-
partisan participants
http://gopkorea.blogs.com/south_korean_politics/

Affiliation network diagram using pages
linked to Lee’s and Park’s sites
N = 901 (Lee: 215, Park: 692, Shared: 6)

Findings & Discussions
• Cyber-balkanization was observed.
– Only a few webpages/sites are shared between
the two campaign sites.
– The campaign sites tend to attract links from like-
minded sites.
• The case study can be taken as an ‘evidence’
to show the existence of the theoretical
correlation between the result of this
particular election and hyperlink network
analysis

Data collection for
the 2007 presidential election
• Co-(in)link analysis of the 20 websites of
the candidates/parties using the Yahoo
– Also web size, incoming links, visitor traffic
• Qualitative complements
• Particularly usefulness: Public opinion
surveys could not be published within six
days before the 2007 election
38

Changes of co-link networks during
presidential campaign period
2 Dec 2007

11 Dec 2007

17 Dec 2007
D-2 day

11 Dec 2007
2 Dec 2007
17 Dec 2007
42

Network Measures of Colink Networks with Three Different Points
Network measures 2 Dec 07 11 Dec 2007 17 Dec 2007
Clustering coefficient 2.581 2.368 1.777
Average distance 1.564 1.821 1.681
(Cohesion value) (0.215) (0.273) (0.346)
Degree centralities
of sites
ijworld.or.kr 0.158 0.263 0.684
leehc.org 0.000 0.053 0.263
ckp.kr 0.000 0.053 0.053
43

Discussions
Should hyperlink data collection be always
conducted using (commercial) search
engines?
How do we know the extent to which a
search engine influences/distorts
research results? Is search engine value-
free research tool?
44

My answer is
• Science organizes, structures, and evaluates
information to develop a systematic body of
knowledge.
• It is up to the researcher to draw the
appropriate conclusions, using his or her
expertise, about the information gathered
from the web using search engines.
• While search engines collect data from the
entire web, finding the truth from the
information is the business of academics
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The end
Thank you for listening, and thank you to my assistants
Han Woo Park, Ph.D.
Email: hanpark@ynu.ac.kr
Website: www.hanpark.net
Partially supported by a Korea Research Foundation Grant
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