Social Network Perspective: Model of Student’s Knowledge Sharing On Social Network Media

Bentar Priyopradono1, Danny Manongga2, Wiranto H. Utomo3
1 Information System Department, Faculty of Information Technology,
Satya Wacana Christian University, Salatiga, Central Java 50711, Indonesia
2 Faculty of Information Technology, Satya Wacana Christian University,
Salatiga, Central Java 50711, Indonesia
3 Faculty of Information Technology, Satya Wacana Christian University,
Salatiga, Central Java 50711, Indonesia

http://www.ijcsi.org/papers/IJCSI-9-3-2-54-58.pdf
Abstract
Recently, the role and development of information technology
especially the internet, gives impact and influence in social
relationship especially for social network site services users. The
impact and influence the use of Internet which is related to
exchange information and knowledge sharing still become one of
the interesting topics to be researched. Now, the use of social
media network by students are the best way to them to increase
their knowledge as communication media such as, exchange the
information or sharing about something. This research describes
about knowledge sharing model of students by using social
network perspective analysis in social network media. Based on
this model, it can be seen if the students can be participated in
social network media.
Keywords: Knowledge Sharing, Social Network Media,
Information Technology, Social Network.
1. Introduction
The main reason people use the internet is aim to can
communicate with others by using email or social network
site. Internet has brought people to be able to use social
network media so that they can interact and communicate
well with friends or others by using social network such as
twitter, facebook, and blog which are broader. There is a
question appear whether social network media has social
interaction relationship between students to exchange the
information or knowledge sharing in supporting students‟
learning.
2. Social Network Analysis
Social Network Analysis (SNA) was developed to
understand the relationship (ties/edge) between the actors
(nodes/points) that exist in a system with two focuses, is
that actors and relationship between actors in a particular
social context. Those focuses help the understanding of
how the position of the existing actors can affect access to
the existing resources such as goods, capital, and
information. It is shows that economic activity is
associated with social structure that eventually led the
concept of social capital.
Information is the most important resource that flows in
SNA network which is often implemented to identify the
flow of information and „bottleneck‟. In theory, by
identifying the information flow and bottleneck, it can help
to increase the strategies that could spur the actors to share
the information instead of creating new strategy [8].
When the actors access the existing resources, they will
form a cluster where the actor with the best position will
get more information than the others. Usually an actor who
has access to various resources is in corporate in the
various clusters, and this will usually give strength / power
because they act as intermediaries for them that their
contacts and access are little. It needs to note is that the
information flow that occurs is not necessarily
commensurate, in the sense that the hierarchy is formed
based on the position of actors in the network.
Network gives access not only to the resources but also to
other actors who can help give value to those resources.
This shows that actors can manage social network to
maximize their benefits by getting closer to the resources
and opportunities that exist. Investment in social relationships to access or mobilize resources to generate
economic income is referred as social capital development.
The concept of social capital is often discussed in an
abstract way. SNA is a tool which can be used to
understand the social relationships that could affect local
development. The aim of the use of the SNA is to visualize
the relationships of different actors, who interact in one
place / particular context. Furthermore, from the result of
the visualization, the SNA can be used to:
1. Identify individual, groups, and units that play a
major role.
2. Distinguish the break down information, bottleneck,
structural holes, and also individual, group, and
insolated units.
3. Exploit the opportunity to accelerate the flow of
existing knowledge, either functionally or
organizationally.
4. Increase patience and reflection on the importance of
informal networks and the ways to improve
organizational performance.
5. Strengthen the efficiency and effectiveness of existing
formal communication channels.
6. Increase peer support / peer relationships and a
network.
7. Enhance innovation and learning for all members of
the organization.
8. Find new strategies to be implemented in the
achievement of organizational goals [8].

2.1 Network
Network is a collection of relations. Formally, the network
has some of the object (in mathematical terms is called a
node) and the mapping or description of the relationships
between the objects (nodes) [6]. One simple example of a
network which can be found and seen is the existence of a
society. The existence of the community can be viewed as
a network of social relations between individuals from one
another and are very complex [2].

2.2 Social Network
In society can be found if there are web and social network.
The social network itself can be defined as the small world
phenomenon that comes from the observation that each
individual is often associated with a short introductory
chain. Chains accumulate to form a relationship of
complex social networks. In simple terms, refers to
Agusyanto [3], social network can be described based on
the components that make it up:
1. “A set of people, object or events; minimal amount to
3 units – which acts as a terminal. Usually
represented by dots, which in the terminology
referred to the actor of node.”
2. “A set of bonds that connect one point to another
point in the network. The line usually represents these
bonds, which is a channel or path. Bond includes a
bond or bond that does not seem apparent. Usually
the bonding that occurs is known as a network
connection or ties “.
3. “Flow, in the diagram depicted by arrows. Describe
something that flows from one point to another,
through a channel or path that connects each node in
the network “.
Principles, which are underlying each of the components,
affiliated with other components, such as:
1. Ties which link one point to another should be
relatively permanent (there is an element of time /
duration).
2. With a series of these bonds led to a set of points that
there could be categorized or classified as single-unit
different from the other entity.
3. There is a certain pattern or something that flows
from one point to another. Channel that should be
through is not occurring as randomly (random).
There is a “law” or rules that arrange the
interconnectedness of each node in the network and also
there is a set of authority and obligations that arrange from
each point (members), the relationship of one point to
another point or the connection of all points with the center
points and so on [3].
3. Terminology Measurement SNA

3.1 Density and Eigenvector
Density is the proportion all of the relationships that exist
in a network. By using density measurements can be
obtained the information about amount of the relationship
that has been created or received by each actor in a
network. By knowing the value of the average (mean) and
number of relationships (Sum) from the connection of
actors in the network, it can be seen the power of
relationships that may occur in the whole network.
Furthermore, the eigenvector approach is an effort to find
the most central actors in the whole network. Eigenvlaue,
explain that the location of each actor in each dimension or
pattern of the relationship global distance. Eigenvector
itself is the collection of the eigenvalue. Here, eigenvector
is aim to see the aspects of the range (distance) as globally
among the actors [5].
3.2 Centrality and Power
One of the measurements in SNA terminology which
is often used to see and measure the role / influence
(power) from the actors in a social network is centrality.
Centrality is a measure to show how important the actor in a network. Implications from the node / actor who became
the center of a network is the actor who has a stronger
capability in connecting members of other networks [5].
In general, to measure the role and influence of actors in a
network can be done by looking at the 3 (three) centrality
measures terminology, there are: Degree centrality,
Closeness centrality, and Betweeness centrality [5].
1. Degree centrality is the degree of presence and actors
position in a social network. Degree of actors
presence can be seen in two kinds, there are:
In Degree: an actor with high In Degree is shows the
role of an actor is very important (prominent actor).
This is because many actors are trying to get
relationship with them.
Out Degree: an actor who has high an Out degree to
imply the actor in a social network as Influential actor
(actor‟s effect). This will be shown if the ability of
the actor who is able to exchange information with
another also recognize and accept their views.
2. Closeness centrality is a measure of how far the
information can be spread from one actor to another.
Moreover, Closeness centrality show the distance
between one actor to another in a network. It will be
easier for the actor to disseminate information in the
network if the value of the proximity is higher. On the
contrary, if the value of proximity is low, then the
distance of the actor with another are far enough, so
that the dissemination of information from the
informants is quite difficult to another actor.
3. Betweeness centrality is a measure that includes how
far a node / actor are able to control / handle the flow
of information between actors in the network. High
betweeness centrality from the actor shows that the
actor has a great capacity to facilitate the interaction
among of them that are connected. Moreover,
Betweenness centrality can also be used to measure
how well the actor able to facilitate their
communication with other actors in a network. As a
result, an actor with a high betweeness value is the
actors who are able to convey the information to
other actors who are not directly connected with them,
but the other actors can be connected to each other.
4. Knowledge Management
Knowledge management is a process that help the
organizations to identify, select, organize, disseminate and
transfer the important information and skills that are part of
the organization in a good way, then it is expected to
organize the knowledge so that can easily be used in
effectively and efficiently. Knowledge management is
focus on the identification of knowledge. It is also can
provide the explanation so that, it can be divided in a
formal way and hope the knowledge management will
increase the reuse of knowledge. Literature which is
related to knowledge management has a different point of
view. In modern times, the organization has realized the
importance of knowledge management strategy so that the
creation of management and knowledge sharing is very
important to become an agenda [11]. Knowledge
management and knowledge sharing is the creation and
transfer of knowledge [10].
5. Knowledge Sharing
Knowledge Sharing arise because of the individuals‟ effort
to transfer knowledge to others in the organization.
Successfulness of the sharing is depend on the ability of
the receiver and the ability to learn [4], knowledge sharing
is based on three factors such as characteristics of the
recipient (such as capacity to absorb, language and
technical knowledge), type of task (routine or non-routine)
and the type of knowledge (continuum Between tacit and
explicit). Absorption may the recipient to understand and
use the knowledge that has been received, where the
capacity is depend on the adequacy of the knowledge is
receiver to understand the context and background of the
problem [4]. Knowledge sharing is an activity that is
common to discuss in knowledge management. Knowledge
sharing is also an important part in knowledge
management. Knowledge innovation is the goal from the
knowledge management but the knowledge innovation
unable to work without the knowledge. Here, sharing and
using the information will speed up the innovation process
and improve the quality of innovation. Knowledge sharing
is also means the knowledge innovation because everyone
has to add his own understanding when sharing knowledge
[1]. Knowledge sharing can involve the individual, team
and organization. The purpose of knowledge sharing is to
transfer knowledge from the individual to the team or the
organization [1], picture of the process of knowledge
sharing can be a part of the contribution from the
knowledge that one of the parts gets the knowledge. It can
be increase their own understanding and they can process it
into knowledge. Knowledge creation can be done by
converting the knowledge which based on the concept of
tacit and explicit knowledge. The implications of
knowledge are able to achieve. It is because not only by
the conversion of knowledge but also through the
knowledge transfer from the individual level to group and
the organization level to another [7].

6. Related Work
6.1 Liao and Xiong
According to Liao and Xiong paper, they developed a
model based on perspective social networking about
knowledge sharing in community (CoPs), they analyze
knowledge sharing CoPs by looking a network density,
network centrality, network structure is found that there is
a strong relationship contributes to the implicit knowledge
transfer and Weak bonding describe explicit knowledge
based on index above [8]. Fig 1 is a portrait model of
knowledge sharing in communities based on social
network analysis.
Fig. 1 A Model of the Knowledge-Sharing Communities of Practice
Based on Social Network Analysis Perspective.
6.2 Weiqin Chen
Based on Weiqin Chen paper, the collaboration data
analysis can help to uncover the important aspects from the
teachers‟ and students‟ cooperation, this paper presents the
method of social network analysis to support collaborative
learning by using knowledge-building system [9]. The
process model of knowledge building has shown on Fig 2
bellow.
Fig. 2 A Model Knowledge Building.
7. Result
Model of knowledge sharing using social network
perspective analysis for the students on social network
media can be seen in Fig 3.
Fig. 3 A Model Knowledge Sharing Student in Social Network Media on
Social Network Analysis Perspective.
From the model above on Fig 3, it can be seen the flow of
information in knowledge sharing at social network media.
Social network media can give support to the knowledge
sharing and also knowledge transfer from the implicit
knowledge and explicit knowledge among the student.
Here, from all over the structure model above, the students
gets the knowledge and do the knowledge sharing through
activities such as publishing, chatting, application sharing,
instant messaging, video call, group discussing on the
social network media. The power and relationships those
model can be seen from the density, eigenvector, degree
centrality and the betweeness centrality that may occur in
the whole network (network).
4. Conclusions
In conclusion, this research describes the model of
knowledge sharing by students using social network
perspective analysis in social network media. The model
can be applied if the student can participate in social
network media. Here, students‟ activities to conduct the
knowledge sharing by using social network media can
collaborate with knowledge through publishing, chatting,
application sharing, instant messaging, video call, and
group discussing.

Acknowledgments
This paper has been finished because the support from my
lectures Dr. Ir. Wiranto Herry Utomo, M.Kom. and Prof.
Ir. Danny Manongga, MS.c., Ph.D. who give the
motivation for trying to write international journal. Thank
you very much.

References
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[2] Agusyanto, Ruddy, 2010. Fenomena Dunia Mengecil –
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[3] Daly & Haahr., 2007. Social Network Analysis for Routing
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[4] Dixon, N. D. 2000. Common Knowledge: How Companies
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[5] Hanneman, Robert A. and Mark Riddle. 2005.
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[6] Kadushin, Charles, 2004. Introduction to Social Network
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[8] Liao, K., Xiong. H, 2011. Study on Knowledge Sharing of
Community of Practice Based on Social Network
Perspective.Scientific Research.
[9] Chen, W. 2009. Social Network Analysis Supporting
Collaborative Knowledge Building.International Workshop
on Social Informatics.
[10] McInerney, Clare. 2002. Knowledge management and the
dynamic nature of knowledge. Journal of the American
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[11] Coakers, Amar, Granados. 2010. Knowledge Management,
Strategy, and Technology: a Global Snapshot.
Bentar Priyopradono a senior student at Magister of Technology
and Information System, Faculty of Information and Technology at
Satya Wacana Christian University Salatiga, Indonesia. Besides
studying for his Magister to achieve M.Cs degree. He got a
bachelor’s degree with a major in information system, Faculty of
Information Systems Satya Wacana Christian University Salatiga
in 2009.
Dhanny Manongga a lecture at Faculty of Information and
Technology at Satya Wacana Christian University Salatiga,
Indonesia. Completed his undergraduate education at the Faculty
of Electrical Engineering Satya Wacana Christian University.
Completed master and doctoral education in the UK. Research
specialization of Prof. Ir. Danny Manongga, MS.c., Ph.D. is in the
field of Artificial Intelegence, Knowledge Management and Social
Network Analysis (SNA).
Wiranto. H Utomo, a lecture at Faculty of Information and
Technology at Satya Wacana Christian University Salatiga,
Indonesia. He got a Master Degree in Computer Engineering at
Gajah Mada University Yogyakarta Computer Science in 2002 and
his Ph.D at Gajah Mada University in 2011. Research
specialization of Dr. Ir. Wiranto Herry Utomo, M.Kom. is in the field
of SOA, java EE, web services, and software engineering.
IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 2, May 2012
ISSN (Online): 1694-0814
http://www.IJCSI.org 58
Copyright (c) 2012 International Journal of Computer Science Issues. All Rights Reserved.

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