1. Influences of Strong Tie with Opinion Leaders in an
Interconnected Network of Korea
Choi, Myunggoon
myunggoon.choi@gmail.com
Department of Interaction Science
in Sungkyunkwan University
is.skku.edu

2. Research Questions
RQ1: For the Korean, what is the relationship between a tie
strength with opinion leaders and the degree of
information exchange?
RQ2: For the Korean, what is the relationship between a strong
tie with opinion leaders and an influence on people who are
on the periphery of the network?
Go to Hypothesis ☞

3. Introduction
Do you think that information inequality exists in the
information society?

4. Introduction
Do you think that opinion leaders are the most important
people in disseminating information as we know?

5. Literature Review
Information Inequality and Information Exchange
 There have been two separate but similar research fields, which are information
divide and digital divide, with one interdisciplinary area, information inequality
(Yu, 2011).
 Early studies of information divide had defined information divide as the
disparity between the less advantaged in society (e.g., the disabled, the poor and
the aged) and mainstreams (Yu, 2006).

6. Literature Review (Cont.)
Information Inequality and Information Exchange
 Van dijk (2000) said that information divide is the inequality that results from
the disparity of possession and usage for information and communication
channels.
 Britz and Blignaut (2001) used the term, information poverty, instead of
information divide, defining it as the situation that social entities (e.g., individuals
and communities) do not have adequate skills, abilities, and materials in
obtaining information.

7. Literature Review (Cont.)
Information Inequality and Information Exchange
 While the discourse on Information Divide has concentrated on the situation to
get information, the research interest of Digital Divide have been concerned for
an access to ICT.
 Since in the society that the adoption rate of internet and computer is too high,
however, it is not sufficient to examine information inequality with variables of
digital divide, a new approach in building theoretical frame is necessary
(Verdegem & Verhoest, 2009)

8. Literature Review (Cont.)
Information Inequality and Information Exchange
 This study is to examine the phenomenon of information inequality based on the
interdisciplinary approach rather than to define two concepts, information divide
and digital divide.
 Information inequality is defined as multifaceted disparity of information
usage and access to digital technologies between individuals and communities in
organizing information resources
(Yu, 2011).

9. Literature Review (Cont.)
Social Network Perspective and Information Exchange
 Social Network Analysis is the study to represent the social structure with actors
(e.g., individuals and communities) and relationships between actors. It helps to
find the patterns of relationships which represent the exchange of resources
between social entities (Haythornthwaite, 2002; Wasserman & Faust, 1994).
 In order to examine how the social network affects to the social behavior such as
an exchange of resources, it is necessary to approach from 1) “relational” or
“Ego-centered” and 2) “Positioned” or “Entire” levels (Burt, 1987;
Haythornthwaite, 1996).

10. Literature Review (Cont.)
Social Network Perspective and Information Exchange
 The pattern of information exchange provide the explanation that individuals
have their own access to and control of information (Haythonthwaite, 1996).
 To understand of the social structure with a relationship of information
exchange may help to explain the disparity of information between individuals
(Johnson, 2007).

11. Literature Review (Cont.)
Opinion Leaders and Influentials Hypothesis
 This study uses the important concept in the diffusion of innovation theory
which describes in neutral position that information inequality is the naturally
occurring phenomenon (Yu, 2011), in order to examine the phenomenon of
information inequality itself.
 The most important people in disseminating information of innovation refer to
opinion leaders in the diffusion of innovation theory.

12. Literature Review (Cont.)
Opinion Leaders and Influentials Hypothesis
 The importance of opinion leaders was re-emphasized as the two-step of flow
theory, which underlines the role of opinion leaders who allow messages from
media easily to disseminate, played an important role in the media sociology
(Katz & Lazarsfeld, 1955/2006).
 Rogers (2003) defined opinion leaders as people who have uneven influences
on behaviors or attitudes of others.
 Chatman (1987) said that opinion leaders are those who play an important role
in transferring information to others. She underlined the role of opinion leaders in
the information environment.

13. Literature Review (Cont.)
Opinion Leaders and Influentials Hypothesis
 However, previous studies of opinion leaders have not given definite
explanations about dissemination of influences of opinion leaders in process of
the diffusion of innovation or information exchange (Watts & Dodds, 2007).
 Watts and Dodds (2007) said that although they modestly agreed on the
importance of opinion leaders, most of social changes are triggered by those
who are easily influenced by opinion leaders, not opinion leaders.

14. Literature Review (Cont.)
Opinion Leaders and Influentials Hypothesis
 Being influential to something in a network depends on a structure of an entire
network, not the characteristics of specific individuals. Thus, it is necessary to
examine local environments as well as environments around opinion leaders and
those who are directly influenced by them (Watts, 2007).

15. Literature Review (Cont.)
Influence, Tie Strength and Multiplexity
 Opinion leaders which involve relationships with objects influenced by them
are possible to be explained by the social network perspective that consider
relationships such as ties and connections (Scott, 2000).
 An influence between two people in a network indicates the degree of cohesion
which represents the strength of relationship between them. That is, the more
intimate relationship they have, the easier they are influenced each other.

16. Literature Review (Cont.)
Influence, Tie Strength and Multiplexity
 The strength of ties is a combination of the amount of time, the emotional
intimacy, and friendliness (Granovetter, 1973).
 Since the strong ties represent the intimate relationships among people, the
strong ties allow the opponents to have strong motivation and reduce uncertainties
in receiving information (Krackhardt, 1992).
 The strong ties in a network of information flow make have more influences on
people who receive information rather than the weak ties (Brown & Reingen,
1987).

17. Literature Review (Cont.)
Influence, Tie Strength and Multiplexity
 Multiplexity is the term that since the relation between two people can consist
of more than one relationship (Monge & Contractor, 2001), there can be multiplex
relationships such as friend, fellow, and neighbor etc. (Burt, 1982; Hansen, Mors,
& Lovas, 2005; Hite et al., 2006) between them.
 One study showed that the behaviors in multiplex and strong relationships can
occur the same way (Brass, Butterfield & Skaggs, 1998). That is, the multiplex
relations indicate the strong relations (Granovetter, 1973).

18. Hypothesis
Hypothesis 1:
In an entire network, the stronger ties people have with
opinion leaders, the more they exchange information
with others.
Hypothesis 2:
In an entire network, there are significant differences
between the groups which include opinion leaders and
those which dose not include them.
Hypothesis 3:
In an eco-centered network, those who have strong ties
with opinion leader have more influences on the
remains in disseminating information.

19. Method
 Measuring Opinion leaders and Tie Strength
 In order to examine the influence of an individual in a network, this study
uses two type of roles for opinion leaders; closure and brokerage (Burt,
Kilduff & Tasselli, 2012).
 UCINET 6.0, a software package for social network data, is easy to
calculate in-degree and betweenness centrality (Borgatti et al., 2002).

20. Method (Cont.)
 Measuring Opinion leaders and Tie Strength
 For measuring the degree of closure, the in-degree centrality was calculated
(Valente, 2010). In-degree centrality indicates a number of ties directed to the
actor.
 For measuring the degree of brokerage, the value of betweenness centrality
was calculated. Betweenness centrality represents the number of times a
subject acts as a bridge along the shortest path between two other objects
(Wasserman & Faust, 1994).

21. Method (Cont.)
 Measuring Opinion leaders and Tie Strength
 Haythornthwaite (2005) explained the relationship between the strength of
ties and media uses, which referred to “Media Multiplexity.” He said that the
more channel between two people maintain, the more influences they have
each other.
 This study define tie strength as multiplexity of media (e.g., face-to-face,
cellphone, Mobile Instant Messenger, and SNS).

22. Method (Cont.)
 Influences of people who have strong ties
with opinion leaders
 This study divides all of members into three groups ;1) Opinion leaders, 2)
People who have strong ties with opinion leaders, and 3) the remainders,
based on media multiplexity.
 Strong ties indicate the relations which use a number of offline and online
channels in communicating with others (Haythornthwaite, 2005). This study
determined the criteria of classification of strong ties as usages of all of
offline and online channels.

23. Method (Cont.)
 Influences of people who have strong ties
with opinion leaders
 Density, and then, was used for examining influences among three groups.
Influences among social entities indicate the degrees of cohesion. The density,
overall measure of cohesion, indicates the degree to which members are
connected to all members of a population (Haythornthwaite, 1996).
 For a valued graph, the density can average the values attached to the lines
across all lines (Wasserman & Faust, 1994).
 This study examines densities among groups of opinion leaders (A), people
who have strong ties with opinion leaders (B), and the remainders(C), by
comparing densities of each group

24. Method (Cont.)
 Information Exchange
 This study modified the Cerise’s six information exchange relationships:
Giving work (GW), Receiving work (RW), Collaborative writing (CW),
Computer programming (CP), Sociability (Soc), and Major emotional
support (MES) (Haythornthwaite & Wellman, 1998).
 Computer programming was excluded from out list of Information
Exchange relationships, since there are a few tasks related to computer
programming in the department of Interaction Science rather than the Cerise.

25. Method (Cont.)
 Questionnaire
 Respondents reported with whom they have contact in a various channels:
face-to-face, cellphone, Mobile Instant Messenger (e.g., kakaotalk, a multiplatform texting application), and SNS (e.g., Facebook, Twitter, Path, and
etc.). They identified 48 IS students from a list of the IS students.
Figure 1. Format of Questionnaire for Media Multiplexity

26. Method (Cont.)
 Questionnaire
 Respondents were asked to with whom they communicate with, modified
by Cerise members’ six information exchanges (Haythornthwaite & Wellman,
1998). Surveymonkey, an online questionnaire tool, was used for collecting
data. It is useful to reach people who are hard to see in the department.
Figure 2. Format of Questionnaire for Information Exchange

27. Method (Cont.)
 Sample
 Total IS graduates Population included 61 members (33 females, 28 males);
4 international students and 57 domestic students, and 9 absences and 52
attendances. However, this study excluded the international students and
those who are absence from school in a survey. Questionnaire completed by
48 of students of the department of Interaction Science in Sungkyunkwan
University.
 The response rate was 0.458 (22 out of 48). They were asked to report the
behavior of information exchange by a specific medium.

28. Method (Cont.)
 Sample
 If all of students report had listed 48 correspondents, there would have been
48 x 47 = 2256 pairs. And if respondents had fully connected with all of
students, the pairs would be (22 – 1) x 48 = 1008 pairs. The number of
respondents gave a total of 410 pairs. The density is 0.1817 (410 / 2256).

29. Method (Cont.)
 Data Analysis Plan
 The rate of information exchange was based on the frequency of
information exchange between two people. Full matrix of 48 x 48 was
created with limited information exchange relationships from 22 members
with 48 students (22 respondents x 48 students).
The most important task was to find opinion leaders in the network of IS
department. After calculating values of in-degree and betweenness
centralities in the information exchange network of IS department, this study
found the opinion leaders which stayed on the top 10% of the two indices
(Valente & Pumpuang, 2007).

30. Method (Cont.)
 Data Analysis Plan
 Then, for testing Hypotheses 1, the regression analysis was conducted with
the degree of Information Exchange and the degree of tie strengths which
represent media multiplexity with opinion leaders. T-test was conducted for
testing Hypothesis 2.

31. Method (Cont.)
 Data Analysis Plan
 Lastly, this study used ANOVA density model for testing Hypothesis 3.
ANOVA density model tests the probability that the density of within-group
differs from all relations of between-groups (Hanneman and Riddle 2005).
That is, it tests whether the relationship of a network is patterned by a
categorical variable. We examine whether the relationships of influence
defined as media multiplexity are patterned by groups of opinion leaders (A),
people who have strong ties with opinion leaders (B), and the remainders(C).

32. Findings
 Opinion leaders and tie strength
Table 1. Descriptive Statistics for In-degree and Betweenness centralities
N
Mean
Std Dev
Minimum
Maximum
In-Degree Centrality
48
77.521
36.247
15.000
149.000
Betweenness Centrality
48
14.375
36.174
0.000
181.707
 There are four opinion leaders among 48 members in the department of
Interaction Science. IS29, whose in-degree centrality is 135 and betweenness
centrality is 177.269, topped the list, followed by IS15 (In-degree = 111,
Betweenness = 181.707), IS48 (In-degree = 139, Betweenness = 26.399),
IS06 (In-degree = 149, Betweenness = 5.551).

33. Findings (Cont.)
 Opinion leaders and tie strength
Figure 3. Indices of In-degree and Betweenness centralities for the department of Interaction
Sciences’ students
200
IS01
IS02
IS03
IS04
IS05
IS06
IS07
IS08
IS09
IS10
IS11
IS12
IS13
IS14
IS15
IS16
IS17
IS18
IS19
IS20
IS21
IS22
IS23
IS24
IS25
IS26
IS27
IS28
IS29
IS30
IS31
IS32
IS33
IS34
IS35
IS36
IS37
IS38
IS39
IS40
IS41
IS42
IS43
IS44
IS45
IS46
IS47
IS48
180
160
140
120
100
80
60
40
20
0
Indegree
Betweenness
 While IS29 and IS15 have low in-degree centralities and high betweenness
centralites, IS48 and IS06 have high in-degree centrality and low
betweenness centrality.

34. Findings (Cont.)
 Opinion leaders and tie strength
 The low in-degree and high betweenness centrality show the characteristics
of brokerage which have relatively equal chances of information exchange
with others.
 The high in-degree and low betweenness centrality represent the
characteristics of closure which exchange information with some specific
individuals in a network.
 They have different features of opinion leaders.

35. Findings (Cont.)
 Opinion leaders and tie strength
Table 2. Media multiplexity with opinion leaders
Opinion Leader, Opinion Leader, Opinion Leader, Opinion Leader,
IS29
IS15
IS48
IS06
Mean
2.448
2.469
1.833
1.448
SD
1.182
1.187
1.449
1.346
 This study made 48 x 48 symmetrical matrix of tie strength based on the
average of media multiplexity between two people. The students in the
department of Interaction Science build relationship throughout more than
one or two channels in an average.

36. Findings (Cont.)
 Influences of opinion leaders in a global level
Table 3. Results of regression analysis for the relationship between tie strength with
opinion leader and the degree of information exchange
β
Opinion Leader
IS29
Opinion Leader
IS15
Opinion Leader
IS48
Opinion Leader
IS06
SE
T
R2
13.453**
15.08
9.38
6.449
4.222**
3.988
3.499
4.099
3.19*
3.78
2.68
1.57
0.195
0.254
0.146
0.056
Note: N = 44, * p < .05, ** p < .01
 Several scholars have emphasized the role of a brokerage which connects
relations between people for opinion leaders (Burt, 1999; Goldenberg et al.,
2009).

37. Findings (Cont.)
 Influences of opinion leaders in a global level
Table 3. Results of regression analysis for the relationship between tie strength with
opinion leader and the degree of information exchange
β
Opinion Leader
IS29
Opinion Leader
IS15
Opinion Leader
IS48
Opinion Leader
IS06
SE
R2
T
13.453**
15.08
9.38
6.449
4.222**
3.988
3.499
4.099
3.19*
3.78
2.68
1.57
0.195
0.254
0.146
0.056
Note: N = 44, * p < .05, ** p < .01
 Betweenness centrality of IS06 (5.551) is lower than the average of
betweenness centrality in the network (Table 1). It means that the low ability
of a brokerage reduce the influence on an overall network.

38. Findings (Cont.)
 Influences of opinion leaders in a global level
 This study compared the degree of information exchange between groups
that include opinion leaders and do not include them for examining
influences of opinion leaders on groups.
 There are 4 laboratories which include opinion leaders out of 10
laboratories in the department of Interaction Science. A number of students in
the group which include opinion leaders are 28, and 20 for the another group.

39. Findings (Cont.)
 Influences of opinion leaders in a global level
 The result showed that the degree of information exchange for the group
which have opinion leaders (M = 91.679, SD = 36.382) is higher than havenot (M = 57.700, SD = 26.424).
 The difference, t(45.9) = -3.73, between two groups proved to be
significant at the p < .001 level.
 Hypothesis 2, “In a whole network, there are significant differences
between the groups which include opinion leaders and those which do not
include them,” was supported.

40. Findings (Cont.)
 Influences of opinion leaders in a local level
Table 5. Densities between and within groupsa of in the ego-network for media
multiplexity
Opinion Leader
29
Opinion Leader
15
Opinion Leader
48
Opinion Leader
06
0.000
0.000
0.000
0.000
A–A
4.000
4.000
4.000
4.000
A–B
1.750
3.152
3.364
1.974
A–C
4.000
4.000
4.000
4.000
B–A
2.938
2.149
1.851
2.250
B–B
1.794
1.758
1.639
2.035
B–C
0.350
0.576
0.455
0.763
C–A
0.575
0.333
0.355
0.592
C–B
0.556
0.273
0.440
C–C
a The groups indicate opinion leader (A), people having strong 0.338
ties with opinion leader (B), and the remains of members (C).
 For testing hypothesis 3, the densities between B and C in the network of
media multiplexity which indicates influences have to be higher than those
between A and C at the significant level.

41. Findings (Cont.)
 Influences of opinion leaders in a local level
Table 5. Densities between and within groupsa of in the ego-network for media
multiplexity
Opinion Leader
29
Opinion Leader
15
Opinion Leader
48
Opinion Leader
06
0.000
0.000
0.000
0.000
A–A
4.000
4.000
4.000
4.000
A–B
1.750
3.152
3.364
1.974
A–C
4.000
4.000
4.000
4.000
B–A
2.938
2.149
1.851
2.250
B–B
1.794
1.758
1.639
2.035
B–C
0.350
0.576
0.455
0.763
C–A
0.575
0.333
0.355
0.592
C–B
0.556
0.273
0.440
C–C
a The groups indicate opinion leader (A), people having strong 0.338
ties with opinion leader (B), and the remains of members (C).
 It is not sufficient to fully support the third hypothesis, because the A - C
densities are higher than B – C for opinion leader 29 and 15.

42. Discussion
 This study examined how opinion leaders influence on individuals at the
global and local level.
 Global Level: An importance of Opinion Leaders in having access and
exchanging information.
-
The stronger ties people maintain with opinion leaders, the more chances
to get information they have.
-
And the degree of information exchange in the groups involving opinion
leaders is much higher than the groups that have not opinion leaders.

43. Discussion (Cont.)
 Local Level: Influences of opinion leaders depending on their role in a
network
-
The opinion leaders as a brokerage have great influences on all of
individuals in exchange information with multiple communication
channels.
-
The opinion leaders as a closure influence just on people who have strong
ties with them.

44. Discussion (Cont.)
 Local Level: Influences of opinion leaders depending on their role in a
network
-
The opinion leaders as a brokerage have great influences on all of
individuals in exchange information with multiple communication
channels.
-
The opinion leaders as a closure influence just on people who have strong
ties with them.
 While we admit the importance of opinion leaders, the finding shows that
people who have strong ties with opinion leaders are more likely to influence
on individuals, depending on types of opinion leaders.

45. Discussion (Cont.)
 Theoretical implication on the studies for opinion leaders:
− This study supports “Influentials Hypothesis” with the empirical case
study of information flow in small organization.
 Practical implication:
− The government has to discover opinion leaders in every field who are
available for multiple communication channels in order to allow people
to access novel information.
− Aral and Van Alstyne (2011) suggest that in the high-dimensional
information society, a brokerage of high communication bandwidth has
an advantage on access to information.

46. Discussion (Cont.)
 Practical implication:
− And it is important for opinion leaders and easily influenced people to
help people to learn how to use information throughout a government
support policy.
− The government must do more to support the regions which have been
insufficient in opinion leaders as a brokerage.

47. Limitation
 While this study has insightful implications, the results of this study should be
interpreted with caution for several reasons.
1.
Conceptualization of personal influence is limited and applied partially.
Weinmann (1991) argued that influences consist of three personal
elements:
1) Personification which represents a specific value relating to
personal characteristics;
2) Competitiveness relating to an intellectual level; and
3) Social position relating to social capital, and social elements.

48. Limitation (Cont.)
 While this study has insightful implications, the results of this study should be
interpreted with caution for several reasons.
2.
The sample of this study is limited as it focused on one specific
organization. This limitation is related to external validity in
generalizing the results for understanding the phenomenon of
information inequality in Korea.

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52. Thank you
Choi, Myunggoon
myunggoon.choi@gmail.com
Department of Interaction Science
in Sungkyunkwan University
is.skku.edu