International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
Analytical Hierarchy Process to explore the
influence of social networking on student’s
academic performance
Addisu Mesfin1, Prof.Shruti Patil2
1
MTech Student, Symbiosis Institute Of Technology (SIT), Pune ,
2
Assistant Professor, Symbiosis Institute of Technology (SIT), Pune 412115, Maharashtra State, India .
Abstract
Social networks have penetrated all ages of internet
users, becoming an efficient way of communication
as well as entertainment, especially in the student
community. This advent has not only impacted the
human lives positively but also created a niche for
some pessimistic activities and behavioral
tendencies. The purpose of this paper is to provide a
quantitative insight on the use of various social
networking sites and their effects on the academic
performance of students. An inverse ratio is observed
between the overall well being of an individual and
the amount of time one spends on the social
networks. This observation is tested with the help of
AHP as a mathematical tool.
The analytical
hierarchy process (AHP) is used as a technique for
arranging and analyzing complicated problems by
using mathematics and psychology. It can use both
prejudiced individual judgments and objective
assessment just by Eigen vector and examining the
reliability of the assessment by Eigen value.
I. Introduction
The internet has given us the ability to connect with
people from around the globe with a few clicks of a
button. You can easily send information to a friend or
get information. Social sites such as Whatsapp,
Facebook, viber, imo etc, have attracted millions of
users, many of whom have integrated these sites into
their daily practices. College students spend a lot of
time on these sites uploading or downloading, getting
information concerning their career or academic
work. Students are always online every second,
chatting with friends, watching online movies,
playing online games, doing research. Social site has
become a habit for some students; they find it
difficult to study for one hour without login to one
social site. Some students have become very smart
because of the information they get from this sites,
why some have become very poor academically,
because it easy to get almost any materials for school
assignment.
Fig 1: Show % of time spent on various networking sites
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
II. Literature review
Different authors have conducted many researches
about influence of social sites on college student’s
academic performance. Most paper result shows:
student higher openness spend more time on face
book. Time spend on face book is strongly or
significantly negative related to all overall GPA.
Some paper shows sharing information is positively
predictive and using face book socializing is
negatively predictive. Face book users scored low
grade than non face book users because face book
users study low hour than non face book users. Time
spend on face book has negative relationship with
time spend to prepare class. Some result shows that
personality is also related to use of social sites. The
No of
paper
Paper title
1
The effects of personality
traits,
self-esteem,
loneliness, and narcissism
on Face book use among
university students
Methodology used



2
3
4
Too much face and not
enough
books:
The
relationship
between
multiple indices of Face
book use and academic
performance
A tale of two sites:
Twitter vs. Facebook and
the personality predictors
of social media usage

Effect of online social
networking on student
academic performance

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majority user of online social networks is college
students. Male were related to SNS than female to
play online games. Females upload more photos and
update their status than male. So, gender has direct
relationship related to SNS use and viewing photos,
comments are spend more time. SNS is decreasing
both efficiency and productivity in academic settings.
Some research concludes that different motivations
are influence to use face book like, photos, videos,
online games etc. There is also the negative
relationship between time spend and use of laptop,
tablet, mobile phone in class. Most college students
use class tasks but they are tend to facebook.
Commonly students use their electronic device to
send text, photo.

Advantage
Disadvantage
Use three of big
five
traits(Neuroticism
(worry)
extraversion (stay
alone)
openness (inner
feeling) use of
face book
North-Eastern US
sample
3866
online in survey
monkey.com(on
facebook)

Reduce
higher
openness spend
more time on face
book.

In this paper study
technology
use
and
academic
performance

Time spend on face book is
strongly or significantly
negative related to all over
GPA
Use
big-five
factors use of the
two largest social
network
sites
(face book and
twitter ) online
Collect survey all
over US area

Develop use of
language(writing
skill)
openness(+ve
correlations)

neuroticism(emotional)
Extraversion(quiet &shy)
Most
USA
students use class
tasks but they are
tend to face book.

Higher attentions span
online social network sites


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
Visit or comment friends
photo, un friends photo on
face book take more time .

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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
5
6
7
The relationships among
the Big Five Personality
factors,
self-esteem,
narcissism, and sensationseeking
to
Chinese
University students’ uses
of social networking sites
(SNSs)
An exploration of social
networking
site
use,
multitasking,
and
academic



paper was write in
china
Survey 265

The result shows
that
Narcissism
and extraversion
were
positively
related to post
photos


Male were related to SNS
play more online games
than female
Females were more update
their status than males

This research give
 SNS is decrease both
pause
to
efficiency and productivity
university admin
in academic settings
and policy makers

to think more
about the use of
SNS related to
education
Personality
and
 Canada
 The
research
 Psychological distress and
motivations
associated
university
of
conclude
that
high level of associated
with Facebook use
south-western
Different
sensitive to treat
Ontario students
motivations
are
at all questioners
influence to use
were
distribute
face book like,
online
photos,
videos,
online games
Table 1: show literature review which are written by different authors in different years
First prepared Dataset, second classify and generate
III. Methodology used for analyzing problem
input/output parameters, third association model and
under consideration
the last verify the model by using AHP. We prepared
Data Collection
We have taken 172 number of students in 4 different
questionnaires to display the main criteria (Attention
departments(computer science ,IT, Civil, M-tech/cs).
Span , Academic competence , Effective time
Among this there were 122 male and 50 female
management , General Awareness , Neuroticism ) ,
students in different batches. A printed hardcopy of
sub-criteria (Questionnaires) and Alternatives
the questionnaire was distributed to them which
(Facebook , Whatsapp , Viber) then as individual
consisted of total 26 questions. Based on the
pairs ask respondents to compare the pair scale
feedback received, a softcopy of dataset was prepared
ranges from 1 to 9 (Saaty, 1980).
which was then processed using AHP. Following
were the steps taken:
Sampled
USA
451 and Europe
406 online from
survey
hosting
website

Fig 2: Workflow of Methodology
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WEKA
WEKA (Waikato Environment for Knowledge
Analysis): is a popular suite of machine learning
software written in Java, developed at the University
of Waikato, New Zealand. It is free software licensed
under the GNU General Public License.
Weka is a workbench that contains a collection of
visualization tools and algorithms for data analysis
and predictive modeling.
Advantages of WEKA
a) Free availability under the GNU General
Public License.
b) Portability, since it is fully implemented in
the Java programming language and thus
runs on almost any modern computing
platform.
c) A comprehensive collection of data
preprocessing and modeling techniques.
d) Ease of use due to its graphical user
interfaces.
Weka supports several standard data mining tasks,
more specifically, data preprocessing, clustering,
classification, regression, visualization, and feature
selection. All of Weka's techniques are predicated on
the assumption that the data is available as one flat
file or relation, where each data point is described by
a fixed number of attributes (normally, numeric or
nominal attributes, but some other attribute types are
also supported). Weka provides access to Excel(CSV
format) SQL databases using Java Database
Connectivity and can process the result returned by a
database query. It is not capable of multi-relational
data mining, but there is separate software for
converting a collection of linked database tables into
a single table that is suitable for processing using
Weka. Another important area that is currently not
covered by the algorithms included in the Weka
distribution is sequence modeling.
Fig 3: Process of Association Model
Association Rule and Predictive Apriori Association
Association Rule of data mining
Association rules are used to find the frequent
Rule.
pattern, association or correlation in transaction
There are 16 questions which were distribute to SIT
database. Association rule mining can be used in
students . Depends on the weka result we got the
Basket Data Analysis. Association Rule algorithms
above results in association Algorithm. Each
are Apriori, Sampling, Partitioning & Parallel
questions use as input, weka uses to combine this
Algorithm. This section describes the Apriori
input questions and process after processing we got
six outputs this are Attention Span, Academic
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
Competency, Effective time management, General
awareness, Neuroticism and Physical health. This six
outputs are not got directly from the questionnaire
but all questions are talk about this six out
puts(Attention Span, Academic Competency,
Effective time management, General awareness,
Neuroticism and Physical health).
Attention Span: is the length of time which a
person is able to concentrate mentally on a particular
activity. And it is the amount of concentrated on can
spend on task without becoming distracted. Your
attention Span can have a major impact at your
performance at work.
Most Students Spend their time on social site
networks this is show that the attention span of
college students in social media is more than
attention span of college students on their academic
activity.
Academic competence: It includes many of the
academic activities like reading, writing, calculating,
solving problems, attending, questioning, and
studying needed for academic success.
The academic performance of college students is
decrease because of the social site networks like
facebook, Whatsapp, Viber etc. Students are stay
more than 4 hours in a day in this sites so they did not
give more time to their academic activities.
Effective time management: It is very important to
college students that you develop effective strategies
for managing your time to balance the conflicting
demands of time for study, leisure, playing and
access internet. Time management skills are valuable
in job hunting, but also in many other aspects of life:
from revising for examinations to working in a
vacation job.
Some of these skills including setting clear goals,
breaking your goals down into discreet steps, and
reviewing your progress towards your goals are
covered in Action Planning.
But because of social sites college students did not
use this Effective time management effectively so,
college students are weak in their academic activities.
General Awareness: It is knowledge or perception
of situation or facts to concern about and wellinformed interest in a particular situation or
development. Having knowledge or discernment of
something that aware of about the difference social
site networks are the main reason to spend our time
which is use to academic activities. Aware implies
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knowledge gained through one's own perceptions or
by means of outside information. All most all college
students have general awareness about the social site
networks but they use this social sites everyday more
than their academic studies.
Neuroticism : Persons are often self-conscious and
shy, and they may have trouble controlling urges and
delaying gratification.
Neuroticism is a prospective risk factor for most
"common mental disorders", such as depression,
phobia, panic disorder, other anxiety disorders, and
substance use disorder symptoms that traditionally
have been called neuroses. So , most social sites like
Facebook ,Whatsapp, Viber etc are the fundamental
cause of neuroticism on college students.
Physical Health : It is critical for overall well-being
and is the most visible of the various dimensions of
health, which also include social, intellectual,
emotional, spiritual and environmental health. Some
of the most obvious and serious signs that we are
unhealthy appear physically. For instance social site
networks are cause of physical health problem like,
Eye problem, Skin problem, Finger problem and
cause of ergonomics.
IV. AHP model for influence of social sites in
student’s academic performance
Users of AHP first decompose their decision problem
in to a hierarchy of more easily sub-problems. Each
can be analysis independently .The elements of
hierarchy can related to any aspect of the decision
problem tangible or intangible.
Once hierarchy is built the decision makers
systematically evaluate its various elements by
comparing them to each other two at a time, with
respect to their impact on an element which are listed
. For example facebook , Whatsapp , Viber Etc. The
decision makers can use correct data about the
elements, but they typically use their judgments
about the elements relative meaning and importance.
AHP uses to convert the evaluation into numerical
value that can be processed and compared the entire
range of the problem. A numerical weight or priority
is derived for each element of the hierarchy, allowing
diverse and elements to be compared to one another
in a rational and consistent way. In the final step of
the process, numerical priorities are calculated for
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
each of the decision alternatives. These numbers
represent the alternatives' relative ability to achieve
the decision goal, so they allow a straightforward
consideration of the various courses of action.
Fig 4: AHP Model Influence of social sites in student’s academic performance
AS/Q6 : Where do you browse
ETM/Q7 : When browse
ETM/Q9 : How many hours go online
AS/Q8 : What do you browse
ETM/Q11 : Why do you choose
AS/Q10 : Most your choose
ETM/Q16: Which Spend more time
AS/Q16 : Spend more time
GA/Q2 : Are you aware this sites
GA/Q11 : Why do you choose
AC/Q7 : When browse
GA/12 : What are effects
AC/Q 9 : How many hours you go online
GA/Q13 : Influence student performance
AC/Q13 : Influence student performance
N/Q12 : What are effects
AC/Q14 : Related to your GPA
N/Q13 : Influence student performance
AC/Q16 : Which Spend more your time
N/Q15 : How to satisfied
All his the above questionnaires are solved in AHP . The results are show in below.
The following three-step procedure provides a good
V. AHP Implementation
approximation of the synthesized priorities.
AHP implementation uses matrix which the
Step 1: Sum the values in each column of the pair
questionnaires are more complex or has more than or
wise comparison matrix.
equal to three alternatives. Around twelve questions
Step 2: Divide each element in the pair wise matrix
have three and more than three chooses. So, AHP
by its column total. The resulting matrix is referred to
implementation is must. The result is show in below:
as the normalized pair wise comparison matrix.
Procedure for Synthesizing Judgments
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Step 3: Compute the average of the elements in each
row of the normalized matrix.
 λmax = Column sum of 1st * weight of 1st
column + Column sum of 2nd * weight of
2nd column + Column sum of 3rd * weight
of 3rd + Column sum of 4th * weight of 4th
column...
------------column x * weight n----(1)
 CI = λmax – n / n-1-----------------(2)
 CR = CI / RI--------------------------(3)
students spend their time on facebook, 10 students
spend their time on (facebook , whatsapp and viber)
and 4 students spend their time on other social sites.
Many students choose whatsapp, their reason is fast
and cheap. Most students browse this sites in hostel,
home, college, café and class. Most students browse
at night. It has influence students performance 121
students said yes, 27 students said no and 24 students
not respond. Most students go online daily. Around
93 students spend 4 or 6 hours in everyday. Most
students use online to chatting, sports(news),
entertainment(game) and education.
The following tables show the summery of the usage
of social sites among respondents or students by
using AHP implementation.
VI. Results
All students have awareness about social sites. 79
students spend their time on (facebook and whatsapp)
,66 students spend their time on whatsapp, 13
Table 2: Random Consistency Index (RI)
n
1
2
3
4
5
6
7
8
9
10
RI
0
0
0.58
0.9
1.12
1.24
1.32
1.41
1.45
1.49
All questionnaires have its own results and recommend which one is best among each questions chooses
What is your Mobile or laptop type?
frequent percentage
Laptop , android phone 131
76.162
others
41
23.84
total
172
100%
Around 76.16% of SIT students are use Laptop and android phones. But 23.83% of students use other devices like
iphone, Apple and some are use either Laptop or Android phone.
Are you aware of social network sites?
frequent percentage
yes
172
100
no
0
0
total
172
100 %
All SIT students which are answered my questionnaires in all batches and departments have awareness to social
sites.
Do you have access to the internet?
frequent
percent
yes
167
97.09
no
5
2.91
Total
172
100%
97.09% of SIT students in have internet access. But around 2.91 % of students have not Internet access because of
different reasons like economically, lack of device which students use to access internet.
How long you have social site profile?
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
more than 3 years
Weight (W)
0.53296088
Vector(V) 100 %
53.29608796
more than 2.5 years
more than 2 years
more than 1 year
0.22856992
0.15016238
0.04415341
22.85699188
15.01623834
4.415340914
More than 6 month
0.04415341
4.415340914
Sum
1
100
λ max
CI
CR
5.231988188
0.057997047
0.051783078
For this implementation, we get the results that more
than 3 years is the best choice, followed by more
than 2.5 years as the second choice, followed by
more than 2 years as the third choice, followed by
more than 1 year as the fourth choice and the worst
choice is More than 6 month.
The composite weights are ratio scale. We can say
that more than 3 years is 12.07 times more preferable
than More than 6 month and more than 1 year , more
than 3 years is 3.55 times more preferable than more
than 2 years and more than 3 years is 2.33 times
more preferable than more than 2.5 years .
The pie chart shown in figure 5 gives details about
different alternatives in terms of their
proportion in how long use social sites.
Fig 5: shows percentage of how long use social sites
The above values can also be verified through MATLAB as shown in figure 6. The snippet in figure 6 shows the
process For the same as excel implementation result.
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Fig 6: Use of MATLAB to verify AHP results for proposed analysis
Most Effects of Social sites
Weight (W)
0.395268962
0.272550306
0.138332298
0.075292037
0.075292037
0.043264361
1
Time consume
Addictive
Eye problem
Discipline
Sleepless
Expensive
Sum
λ max
6.067509105
CI
0.013501821
CR
0.010888565
Vector (V) %
39.5268962
27.25503059
13.83322976
7.529203692
7.529203692
4.326436068
100
For this implementation, we get the results that Time consume is the best choice, followed by Addictive as the
second choice, followed by Eye problem as the third choice followed by Discipline as the fourth choice, followed by
Sleepless as the fifth choice and the worst choice is Expensive. The composite weights are ratio scale. We can say
that Time consume is 9.14 times more preferable than Expensive , Time consume is 5.25 times more preferable than
(Sleepless and Discipline) , Time consume is 2.86 times more preferable than Eye problem and Time consume is
1.45 times more preferable than Addictive.
The pie chart shown in figure 9 gives details about different alternatives in terms of their proportion in most effects
of social sites in students performance.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
Fig 7 : Show percentages the most effects of social sites.
The above values can also be verified through MATLAB as shown in figure 10. The snippet in figure 10 shows the
process For the same as excel implementation result.
Fig 8 : Use of MATLAB to verify AHP results for proposed analysis
Which one is spend more your time?
Facebook
Others
Whatsapp
Facebook, Whatsapp
Weight (W)
0.456936795
0.25564231
0.244772745
0.04264815
Vector (V)100 %
45.69367948
25.56423104
24.47727452
4.264814961
Sum
1
100
λ max
4.024527796
CI
0.008175932
CR
0.009084369
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
For this implementation, we get the results that Facebook is the best choice, followed by Others as the second
choice, followed by Whatsapp as the third choice and the worst choice is Facebook, Whatsapp. The composite
weights are ratio scale. We can say that Facebook is 10.71 times more preferable than (Facebook, Whatsapp) ,
Facebook is 1.86 times more preferable than Whatsapp and Facebook is 1.78 times more preferable than Others.
The Total Final Results are:
Weight (W)
Vector(V) 100 %
Academic Competence
0.393134702
39.31347018
General Awareness
0.287317351
28.73173509
Attention Span
0.130690291
13.06902907
Neuroticism
0.130690291
13.06902907
Effective Time mgt
0.058167366
5.81673659
Sum
1
100
λ max
5.164594451
CI
0.041148613
CR
0.036739833
For this implementation, we get the results that Academic Competence is the best choice, followed by General
Awareness as the second choice, followed by Attention Span as the third choice, followed by Neuroticism as the
fourth choice and the worst choice is Effective Time mgt.
The composite weights are ratio scale. We can say that Academic Competence is 6.76 times more preferable than
Effective Time mgt, Academic Competence is 3 times more preferable than (Neuroticism and Attention Span) and
Academic Competence is 1.37 times more preferable than General Awareness.
The pie chart shown in figure 11 gives details about different alternatives in terms of their proportion in which the
final result of effect of social sites.
Fig 9: Show percentages that the final result uses of influence of social sites.
The above values can also be verified through MATLAB as shown in figure 12. The snippet in figure 12 how the
process For the same as excel implementation result.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
Fig 10: Use of MATLAB to verify AHP results for proposed analysis
VIII. CONCLUSSION
Identify why most students use social sites specially
facebook and whatsapp. Most researchers are focus
only on Face book. But we included other social sites
like Whatsapp, Viber also .Most the papers shows
only sample results manually. They didn’t use any
data mining techniques. Prediction or AHP
implementation is necessary because the data is very
large. Without data mining prediction and AHP, the
output is not correct or it shows only highlight
results. Then we gave recommendation effect of the
use of social sites and what is the solution one to
minimize our time spend. The final result shows
facebook is most time consuming as compared to
whatsapp and viber because facebook has different
pages, student visit their friends photo, video , play
online games which their friends invite etc. Finally
this are the main AHP implementation results related
to students academic performance and other events.
1. The first composite weights ratio scale are : We
can say that Academic Competence is 6.76 times
more preferable than effective time mgt, academic
competence is 3 times more preferable than
(Neuroticism and Attention span) and academic
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competence is 1.37 times more preferable than
aeneral awareness.
2. The second composite weights ratio scale is: We
can say that time consume is 9.14 times more
preferable than expensive, time consume is 5.25
times more preferable than (Sleepless and
Discipline), time consume is 2.86 times more
preferable than Eye problem and time consume is
1.45 times more preferable than addictive.
IX. Reference
[1]
[2]
[3]
[4]
[5]
Aryn C. Karpinski et al (2013) An exploration of social
networking site use, multitasking, and academic performance
among United States and European university students.
Craig Ross *, Emily S. Orr, Mia Sisic, Jaime M. Arseneault,
Mary G. Simmering, R. Robert Orr (2009) “Personality and
motivations associated with Facebook use”.
David John Hughes a et al (2012) A tale of two sites: Twitter
vs. Facebook and the personality predictors of social media
usage Heyam A. Al-Tarawneh (2014) The Influence of
Social Networks on Students’ Performance.
Jason L. Skues et al (2012) The effects of personality traits,
self-esteem, loneliness, and narcissism on Facebook use
among university students.
Jin-Liang Wanga,b et al (2012)The relationships among the
Big Five Personality factors, self-esteem, narcissism, and
sensation-seeking to Chinese University students’ uses of
social networking sites (SNSs).
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 9- March 2016
[6]
[7]
[8]
Jomon Aliyas Paul et al (2012) Effect of online social
networking on student academic performance.
Napoleon, Egedegbe (29 may 2013) The Effect of Social
Networking Sites on Students' Academic Performance in
Girne American University, North Cyprus
Reynol Junco (2012)Too much face and not enough books:
The relationship between multiple indices of Facebook use
and academic performance.
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[9] Dr. Saaty, Book ,AHP Tutorials .Doc.
[10] Suhas Machhindra Gaikwad et al ( December 2015)
Analytical Hierarchy Process to Recommend an Ice Cream to
a Diabetic Patient Based on Sugar Content in it.
[11] Wikipedia
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