How to social scientists use link data (11 june2010)

WCU
WEBOMETRICS
INSTITUTE
INVESTIGATING INTERNET-BASED POLITICSS WITH E-RESEARCH TOOLS

Use of search engine data to understand
Internet-based political and electoral communication?

Dr. Han Woo PARK
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

Principal Investigator of WCU Project:
Investigating Internet-based Politics with e-Research Tools.

A paper accepted for presentation to the 2010 annual conference of ICA (International Communication Association) held in
Singapore, http://www.ica2010.sg

Abstract
As link data become more available from search engines, the data can play an important
role in understanding socio-political activities in cyberspace.

Internet-based political and electoral
communications conducted in Korea,
where online communication is among the
most well-established in the world.
Advantage Disadvantage
link data collected from link data have some
search engines have weakness, such as
several merits for reliability issues: internal
political communication Two case
algorithms are not made
research, including in public and there are
inexpensive access to inconsistencies among
web resources and ease search engines.
of use.

Key worlds: case studies to draw conclusions about the use of link data drawn from
Two
search engine, search engines for research method, political communication,
link analysis, social science purposes.
online research method

WCU
WEBOMETRICS
INSTITUTE
INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS

Introduction
Web traffic is only one part of online communication. There are other significant communication
behaviors on the Internet that could be captured by researchers using publicly available tools.
The Myth of Digital Democracy, Hindman (2008)

political and electoral These bits of online In this study, we are
The Internet is communication is information produced mostly interested in
growing at an undergoing a significant and inscribed via links examining and
transformation because are explicitly or
enormous
Internet-mediated implicitly connected to
evaluating the
rate in terms
communication has each other by topics of practices and trends of
of recorded
digital traces. rapidly become popular interest and have online political
among government become a useful communication by
officials, politicians, and resource for
citizens. researchers. examining the ‘linking’
behavior involved.

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WEBOMETRICS
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Introduction
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.
Two case studies of Internet-based political and electoral communications conducted in Korea.

Case 1.
Examines the online characteristics of the 2007 presidential election in Korea.
We analyze a substantial amount of link data obtained using search engines in order
to understand their broader political implications.

Case 2.
Examines how search engine-based methods are useful in discovering connections
among Korean legislators in the online social networking sphere in Korea.

These cases reveal that link data collected from search engines have merits for
political communication research. The following discussion looks at the pros and cons
of search engines as research tools and the use of link data collected from search
engines.
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Background Information and Relevant Literature

The web is constantly growing in terms of content, search engines play the role of information
intermediaries for the web, which has become an important part of public dialogue.

In research analyzing the e-science landscape using statistics about individual keyword
queries via Google, Meyer and Schroeder (2009) found that the search pattern for the
term ‘cyberinfrastructure’ reveals which U.S. regions are deeply involved in national e-
science projects, such as major supercomputing centers. Further, using Google-generated
keyword activity data, Varian and Choi (2009) showed that public data from search engines
helped improve economic forecasts for various industries, including automobile
sales, home sales, retail sales, and travel behavior.

Thelwall (2004) Search engines allow researchers to get materials from a much wider
range of subjects than previously available through traditional library databases. One
important contribution of search engines is the ability to retrieve relevant web-based
materials using hypertext links, enabling researchers to gather and recombine information
collected from the Internet.

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Background Information and Relevant Literature

Elgesem (2008, p.239) argued that “search engines are objective in the sense that
these engines try to be consistent with their own stated policies.” With respect to
coverage and consistency, problems may occur due to the nature of the unstructured
web. In other words, the lack of reliability may not be caused by the search engine.

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 (Caldas
et al., 2008).

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Case 1. 2007 Korean Presidential Election
Background
Korea boasts the highest proportion of broadband users in the world, and there is a
unique evolution of online culture in Korean cyberspace. The country’s impressive level
of technological development includes a vibrant online communication environment.

The online political climate during the 2007 Korean presidential election can be
examined effectively using web-based data analysis. In particular, there were 12
candidates who ran for president and several parties were created in 2007 to
support these candidates (see Table 1). The candidates and the parties had to
compete against each other to win public attention, particular since it was difficult
for citizens to differentiate their stances on issues.

Particularly useful for web analysis was the fact that public opinion surveys could not
be published within six days before the 2007 election. In 2002, surveys could not be
published within 22 days of the presidential election. We will examine how the
popularity of individual candidates and parties developed during the 2007 presidential
election campaign in South Korea using web-based data collection.

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Background

Table 1. Websites of Presidential Candidates and Parties
Candidate Website Candidate’s Party Website
Lee Myung-Bak (Lee MB) www.mbplaza.net Grand National Party (GNP) www.hannara.or.kr

Chung Dong-Young (Chung DY) www.cdy21.net United New Democratic Party (UNDP) www.undp.kr

Lee Hoi-Chang (Lee HC) www.leehc.org Independent

Moon Kook-Hyun (Moon KH) www.moon21.kr Creative Party (CKP) www.ckp.kr

Kwon Young-Ghil (Kwon YG) www.ghil.net Democratic Labor Party (DLP) www.kdlp.org
Rhee In-Je (Rhee IJ) www.ijworld.or.kr Democratic Party (DP) www.minjoo.or.kr

Huh Kyung-Young (Huh KY) Same as party site Economy & Republican Party (ERP) www.gonghwa.com

Geum Min (Geum M) www.minnmin.net Socialist Party (KSP) www.sp.or.kr

Chung Kun-Mo (Chung KM) www.bestjung.kr True Owner Coalition (TOC) www.chamjuin.or.kr
Chun Kwan (Chun K) www.chamsaram.or.kr Chamsaram Society Full True Act Same as candidate site
(CSFTA)
Sim Dae-Pyeng (Sim DY) www.dpsim.co.kr People First Party (PFP) www.mypfp.or.kr

Lee Soo-Sung (Lee SS) www.leesoosung.com People’s Coalition (PC) Same as candidate site

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Data collection

Subject investigated:
The web presence of all 12 candidates and their parties during the official campaign
period of the 2007 Korean presidential election.

Date:
The online visibility of each party and candidate was measured with colink data, which
refer to incoming links shared between any pair of candidates’ or parties’ websites.
These data were collected at multiple points during the election period from search
engine indexes.

Acquisition time:
Colink data were gathered in three-day intervals, 29 November - 17 December in 2007
(the election was held in 19 December 2007).

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Analytic technique

The process of generating a colink matrix is as follows (for detailed procedures, see
Thelwall, 2009).

First, an input file, which lists a set of colink queries to retrieve webpages sending at
least one link to a pair of website addresses under investigation, is made using a text
editor program (e.g., NotePad).

Second, a symmetrical website*website matrix is created.

Third, the resultant sociogram reveals which sites are central and peripheral.

Fourth, key social network measures are calculated to analyze the overall structure of
colinks: clustering coefficient, geodesic distance, and degree centrality (For the detailed
explanation of network metrics, see Wasserman & Faust, 1994; Park &
Leydesdorff, 2009).

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Analytic technique

As Park (2003) stated in his seminal article titled “Hyperlink network analysis: A new
method for the study of social structure on the web,” link data can be examined using
social network analysis.

The clustering coefficient indicates the degree to which friends (in this case,
neighboring websites) of a person know each other; average distance value shows the
degree of separation on average between each (reachable) pair of websites in terms
of geodesic distance that is defined as the shortest path. The average distance is often
reported with an overall cohesion value between 0 and 1. Larger values indicate
greater cohesiveness.

Degree centrality is a basic and primary measure to indicate the position of a website
based on its interconnections with other websites in a given network. Due to space
limitations, only three websites used in this study were reported in Table 2.

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Findings

The results from the colink data and its accompanying qualitative investigation
indicate the following. The hyperlinked relations among the candidates and parties
over time reflect their positioning in the electoral race and the general climate of
offline politics.

In Figure 1, squares represent candidates’ sites and circles represent parties’ sites.
The thickness of the lines connecting them is drawn bigger in accordance with the
number of external colinks directed to a pair of sites.

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Findings
Since the snapshots taken in December 2007 display distinctive changes, we focus on these dates in the
results section. On 2 December, we can see clearly that parties are clustered with other parties and
candidates are closely linked with other candidates. However, 9 out of 20 sites were not included in the
network. Isolated candidate and party sites are located in the upper left-hand corner of the diagram. During
the initial stage of the campaign, online attention focused on major parties and candidates, as Figure 1
shows. Overall, the network structures among candidates and parties seemed to be loose.

Figure 1: 2 Dec 2007

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Findings
From the network diagram captured on 11 December, it is clear that the Lee HC (leehc.org) website was successful
in catching up with other major candidates’ websites. As a matter of fact, he became one of the major candidates.
He took third position in the presidential race by gaining 15.1% of the total votes. But, he entered the race late
relative to other major candidates and ran without support from a specific party. As seen in Figure 2, he was finally
included in the user-driven networking zone. Another interesting finding on 11 December is the position of
ijworld.or.kr (Rhee IJ’s site) and ckp.kr (CKP’s site).
In the 2 December figure, ijworld.or.kr was only connected to the party site (minjoo.or.kr), but it later became
linked with progressive candidate Chung DY’s site (cdy21.net). The reason is that Rhee IJ had been strongly urged by
the public to give up his candidacy in support of Chung DY. In the case of ckp.kr, this website showed a dramatic
turnaround as its candidate’s (Moon KH, moon21.kr) popularity increased.


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Findings
Figure 3, captured on 17 December, shows that, at the end of the campaign period, a total of 14
candidates and parties joined the user-driven networks. As election day approached, the number of
isolated sites noticeably decreased from 9 (2 Dec) to 5 (17 Dec), which reflected increasing online public
awareness of the election.
Two candidates, Lee HC (leehc.org) and Rhee IJ (ijworld.or.kr), seemed to be on their way to success
because they were fully included in the network. President-elect Lee MB (mbplaza.net ) and his party
(hanara.or.kr) were in the center of the candidate and party group networks, respectively. Overall, the
figures show that as time progressed, link density increased.

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Findings
In addition to the three figures, other network measures between nodes were examined, as
summarized in Table 2. The clustering coefficient that measures the cohesiveness of the network
was 2.581 in the beginning of the official campaign (2 Dec), but dropped to 1.777 two days before
the election (17 Dec). Next, while average reachability scores in terms of geodesic distance
between pairs show some fluctuation, cohesion values in parenthesis clearly indicate that the
network became dense (0.215 -> 0.273 -> 0.346). Average distance values lengthened in accordance
with the gradual influx of isolated sites into the network. Lastly, three websites in particular showed
an increase in their degree centralities.
Table 2. Network Measures of Colink Networks with Three Different Points
Network measures 2 Dec 2007 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

Note: Data were dichotomized for the calculation of clustering coefficient and geodesic distance values, and degree
centralities were normalized for comparison across networks.

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Case 2. Cyworld Mini-hompies of Korean Legislators
Background

The sample for the social networking sphere (Figure 4) is drawn from the Cyworld
mini-hompies (mini-homepages) maintained by members of the 18th National
Assembly.
Cyworld is a Korean web-based social networking service launched on 1 September
1999 .
“Cy” means both “cyber” in English and “relationship” in Korean. Internet users form a
buddy relationship with each other through a service called “mini-hompy,” where they
can decorate their “home” and invite friends using a photo gallery, video clip, message
board, guestbook, friend list, and personal bulletin board. It is similar to the U.S.-
based Facebook and MySpace sites.
In a study of blogs of Korean legislators, Park and Kluver (2009) stated that the mini-
hompies are not only popular with Korean youth, but also with many older Koreans.
Cyworld is Korea’s dominant social networking site, with 90% of young people in their
20s and 25% of the total South Korean population registered as users. According to
the study, South Korean politicians have also begun to make significant use of blogs
and mini-hompies to expand their “personal communities.”

WCU
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INSTITUTE Case 2. Cyworld Mini-hompies of Korean Legislators

Data collection

As of 16 March 2009, 83 out of a total of 295 National Assembly members run their own
mini-hompies. The distribution of the 83 members is as follows: 47 from the GNP (Grand
National Party, the ruling party, Han-na-ra in Korean), 19 from the DP (Democratic Party, the
major opposition party, Min-joo in Korean), 8 from the LFP (Liberty Forward Party, Jayu
Seonjindang in Korean), 2 from the PPA (Pro-Park Alliance, Chinbak Yeondae in Korean), 2
from the DLP (the Democratic Labor Party, progressive party, Min-joo-no-dong in Korean), 1
from the CKP (Creative Korea Party, Changjo Hangukdang), and 4 independents. We obtained
the members’ mini-hompy URLs through official websites and commercial search engines.

We were interested in the legislators’ interpersonal social networking in cyberspace.
However, it is difficult to trace personal relationship among politicians because “friends” on
mini-hompies are confidential.

Three datasets with respect to the status of legislators’ mini-hompies were collected: 1)
date of creation, 2) number of visitors, and 3) frequency of bookmarking by other mini-
hompy users. These data were manually collected. Legislators who did not indicate the
creation date of their sites public were excluded. As a result, we collected data on
links, creation date, number of visitors, and bookmarks for 70 Korean politicians.

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Analytic technique

The same procedures described earlier have been applied to this case study.
Regarding social network analysis, betweenness centralities were measured in
addition to degree centralities. While degree centrality measures a relational
attribute of an actor in a network (e.g., popularity, activity, and prominence in
the flow of information), betweenness is a useful index to measure the
potential influence of the actor in controlling and coordinating communication.
Additionally, we have examined the association between network centralities
and traffic activities.

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Findings

Thirty out of 70 Cyworld-connected legislators were included in the colink network; 40
politicians operated isolated websites.

Lines between the websites indicate the presence of colinks between mini-hompies,
the thickness of lines indicates the number of colinks, and colors represent the
different parties. The size of the label (that is, the politician’s web address) is in
proportion to the number of bookmarks, and the size of the node corresponds to the
number of visitors. The map clearly distinguishes relatively peripheral groups (sparely
linked politicians) from central ones (densely connected politicians) in Korea.

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Findings
Table 3. Normalized Measures of Individual Politicians
The network Name Cyworld_URL Degree Betweenness Visitors Bookmarks Party
centralities and Kang GG kanggigap 28.986 0.005 119.36 0.21 DLP
Kwon YG kwondlp 27.536 0 92.87 0.08 DLP
traffic information
Kim MS kimmoosung 14.493 0 4.98 0.00 GNP
for the 30 Assembly Kim YS kimyoungsun1 42.029 3.649 19.76 0.02 GNP
members’ mini- Kim UD kimeuldong 26.087 0 88.08 0.13 PPA
Kim JP jinpyo415 28.986 0.005 41.04 0.04 DP
hompies are Na KY KyoungOne 28.986 0.005 502.42 0.44 GNP
presented in Table 3. KP npil2580 28.986 0.005 32.32 0.05 GNP
Park GH ghism 42.029 3.649 4524.34 5.89 GNP

Notes:
Seo BS sbs8680 14.493 0 3.91 0.00 GNP
Song YS peacekeeping 14.493 0 28.33 0.02 PPA
http://www.cyworld Ahn HJ masanjun 14.493 0 7.35 0.00 GNP

.com was omitted Won HY
Won HR
whywon21
wworld
28.986
28.986
0.005
0.005
9.28
86.71
0.01
0.17
DP
GNP
in front of the Yoo SM ysm21com 14.493 0 11.70 0.01 GNP
URLs in the table. Yoo JB ilovegimpo 14.493 0 6.47 0.00 GNP

Visitors and
Lee KJ yeskj1 28.986 0.005 15.08 0.02 DP
Rhee IJ ij21 28.986 0.005 17.96 0.02 Indy
bookmarks were Lee HC chang2007 27.536 0 2726.29 1.34 LFP

divided by the Chung MJ
Chung Sk
globalmj
skchung21
28.986
28.986
0.005
0.005
87.14
23.07
0.19
0.03
GNP
DP
number of days the Chung JS jangseon 28.986 0.005 6.55 0.00 DP
Cyworld mini- Cho KT boss110 28.986 0.005 138.22 0.13 DP

hompies were in
Joo SY doitnow304 14.493 0 59.64 0.03 GNP
Chin SH sheechin 28.986 0.005 19.26 0.02 GNP
existence. Cha MJ sosacha 28.986 0.005 26.40 0.01 GNP
Han SK hsunkyo 14.493 0 53.54 0.11 GNP
Hong JP jphong21 28.986 0.005 61.89 0.05 GNP
Hwang WY hwangwygrace 28.986 0.005 8.44 0.01 GNP
WCU
Hwang JH uncinc 14.493 0 7.50 0.00 GNP
WEBOMETRICS

Findings
As seen in Figure 4, the network structure shows a clear butterfly pattern. There is one hub (ghism)
that belongs to Park Gyun-Hye (Park GH, www.cyworld.com/ghism), the daughter of ex-president
Park Jeong-Hee and one of two major GNP candidates (along with president-elect Lee MB) in the
2007 presidential race.
Figure 4: Cyworld Mini-hompies of Korean legislators

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Findings

Table 4 demonstrates that the magnitude and direction of the association between
several centralities and two other variables—visitors and bookmarks—are significantly
correlated.

Table 4. Pearson’s coefficient

Betweenness Visitors Bookmarks
Degree .572(**) .390(*) .420(*)
Betweenness .572(**) .665(**)
Visitors .945(**)

** Correlation is significant at the 0.01 level (1-tailed).
* Correlation is significant at the 0.05 level (1-tailed).
N=30 (Isolated politicians were excluded in this analysis)

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Discussion and Conclusion

This analysis of the linking patterns among Korean politicians’ websites reveals some
interesting facets of how search engine data can be used to map Korean Internet-
mediated political culture. Our findings demonstrate that online markers of political
communication, in the form of hyperlinks, exhibit the significant characteristics that
drive many other phenomena in Korean presidential elections: the networked practices
of politics and affiliations among politicians.

Questions that require further exploration include:

1)Can we trust available search engines, and, if not, what can we do
about them? If we are able to gain access to the search process and how
websites are ranked, can this problem be solved?

2) How do we deal methodologically with the complexity of Web 2.0
using current search engine mechanisms that do not properly index
multimedia content? Do we need new search tools for Web 2.0?

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Lessons for Future Tracking and Mapping Research

What are the lessons from this particular exercise for mapping and tracking online political
communication in the future?

First, some forms of political information exchange are difficult to study only using
search engine results.

Second, qualitative analysis is also necessary because every country has different
web characteristics.

Third, although we analyzed link data using social network measures and visualizations,
this study is descriptive and topological.

Fourth, the purpose of this article was to introduce social science readers to the
methods of search engine-mediated data collection for political research using social
network measures and visualizations.

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WEBOMETRICS
INSTITUTE
INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH
TOOLS

THE END
Thank you for listening, and thank my assistants (Ting Wang)

•Park, H. W. (2011 forthcoming). How do social scientists use link data from search
engines to understand Internet-based political and electoral communication. Quality &
Quantity

•The author would like to thank Bernie Horgan, Rob Ackland, Jeong-Soo Seo, and Yeon-ok
Lee for their helpful comments on an earlier draft. Part of this research was carried out
during the author’s stay at the Oxford Internet Institute.
•During the preparation of final manuscript, this research is supported from the WCU
project granted from South Korean Government. (No. 515-82-06574). http://english-
webometrics.yu.ac.kr

How to social scientists use link data (11 june2010)

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