4.0 A in the questionnaire which consists

4.0
INTRODUCTION

Under this chapter, it will focus on the result
of the research findings. The findings of the research are all based on the
answer given by the respondents through the randomly distributed questionnaire
to 110 respondents during the stage of data collection method.

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4.1
FREQUENCY ANALYSIS

For this part, the frequency distribution that
is represent is based on Section A in the questionnaire which consists of
demographic profile such as age, gender, race, marital status, number of social
media owned, frequency of sharing through social media, main reason for using
social media, and types of people that share.

 

 

Table 4.1.1: Summary on Demographic Profile

Items

Frequency

Percentage (%)

AGE:

19
– 25

13

11.8

26
– 33

66

60

34
– 40

27

24.5

41
– 47

4

3.6

GENDER:

Male

36

32.7

Female

74

67.3

RACE:

Malay

38

34.5

Chinese

52

47.3

Indian

16

14.5

Other

4

3.6

MARITAL
STATUS:

Single

68

61.8

Married

42

38.2

NUMBER
OF SOCIAL MEDIA OWNED:

1
– 3

34

30.9

4
– 6

59

53.6

7
– 10

17

15.5

FREQUENCY
OF SHARING THROUGH SOCIAL MEDIA:

Rarely

5

4.5

Seldom

34

30.9

Sometimes

54

49.1

Frequently

17

15.5

MAIN
REASON FOR USING SOCIAL MEDIA:

Social
Networking

34

30.9

Business
Networking

34

30.9

Finding
Information On Current Issue

42

38.2

TYPES
OF PEOPLE THAT SHARE:

Altruist

11

10

Hipster

14

12.7

Boomerangs

3

2.7

Connectors

30

27.3

Selective

52

47.3

 

Table 4.2 shows the demographic
profile obtained from the respondents. It consists of age, gender, race,
marital status, number of social media owned, frequency of sharing though
social media, main reason for using social media and types of people that share.

Under the first item which is age
ranges, 19 to 25 years old the frequency is 13 with the percentage of 11.8%.
For the age 26 to 33 years old the frequency is 66 with the percentage of 60%.
For the age 34 to 40 years old the frequency is 27 with the percentage of
24.5%. As for the age 41 to 47 years old the frequency is 4 and the percentage
is 3.6%.

Second item is gender. For male, the frequency is 36 and the percentage is 32.7%.
For female the frequency is 74 and the percentage is 67.3%.

Third item is race. For Malay, the frequency is 38 with the percentage of 34.5%.
For Chinese, the frequency is 52 with the percentage of 47.3%. For Indian, the
frequency is 16 with the percentage of 14.5%. As for the Other Races, the
frequency is 4 with the percentage of 3.6%.

The fourth item is marital status. For the single, the
frequency is 68 with the percentage of 61.8%. For As for married, the frequency
is 42, with the percentage 38.2%.

Fifth item is number of social media owned. For the amount ranges from 1 to 3,
the frequency is 34 with the percentage of 30.9%. The second range of 4 to 6,
the frequency is 59% with the percentage of 53.6%. As for range of 7 to 10, the
frequency is 17 with the percentage of 15.5%.

The sixth item is frequency of sharing through social media.
For the first item, which is rarely, the frequency is 5 with the percentage of
4.5%. For seldom, the frequency is 34 with the percentage of 30.9%. For
sometimes, the frequency is 54 with the percentage of 49.1%. As for frequently,
the frequency is 17 with the percentage of 15.5%.

The seventh item is the main reason for using social media. For
social networking, the frequency is 34 with the percentage of 30.9%. For
business networking, the frequency is 34 with the percentage of 30.9%. As for finding
information on current issue, the frequency is 42 with the percentage of 38.2%.

The last item is the types of
people that share. For altruist, the frequency is 11 with the percentage of
10%. For hipster, the frequency is 14 with the percentage of 12.7%. For
boomerangs, the frequency is 3 with the percentage of 2.7%. For connectors, the
frequency is 30 with the percentage of 27.3%. As for selective, the frequency
is 52 with the percentage of 47.3%.

 

 

 

 

 

 

4.2 DESCRIPTIVE ANALYSIS

Table 4.2.1
Social Media Risks Through Information Sharing

 

 

N

Mean

Std. Deviation

 

I am aware that risk will
increase from sharing information through the Social Media.

110

4.6909

0.46423

 

Enabling the firewall does not really stop any
malware or viruses to enter into my system.

110

4.4273

0.49695

 

Reputational risk is the most devastating type of
risk in cyber sharing rather than financial risk.

110

3.2273

0.91530

 

Posting something bad about my company on the Social
Media would affect its’ reputation.

110

4.5273

0.50154

 

Promoting negativity about the company that I worked
for may cost me my career.

110

4.5636

0.49820

 

I always clicked on a pop-up advertisement that is
attractive for me.

110

1.9182

0.94947

 

Sharing secrets should only be made with best
friends.

110

4.0818

0.70557

 

Valid
N (listwise)

150

 

 

 

 

Table 4.2.1 shows the descriptive analysis for social media risks
through information sharing. The variable have seven mean score analysis for
social media risks through information sharing that represent seven statements.
Based on the table, the highest mean is 4.6909, with the statement of “I am aware that risk will
increase from sharing information through the Social Media”. The score represents most of the respondents who were positively
agreed with the statement that risks will increase from sharing information
through social media. The lowest mean is 1.9182 where the statement is about “I always clicked on a pop-up advertisement that is
attractive for me”.

 

 

 

Table
4.2.2: Privacy

 

 

N

Mean

Std. Deviation

 

When signing up to a social site, I always read the
terms first before checking on the Privacy Policy box.

110

2.6273

1.20289

 

I always connect/linked my current social media with the other social sites
(e.g: Instagram & Facebook)

110

2.5455

1.29669

 

I am aware that users of the other social sites will be notified
if I post something on linked sites.

110

4.3364

0.74535

 

Posting latest expensive purchases does not
necessarily have a high tendency of getting robbed.

110

2.1091

1.11984

 

Sensitive data is required before acquiring some
random giveaways.

110

3.7182

0.83646

 

I always leave my personal information open to the
public on sites like Facebook.

110

2.0455

1.07845

 

Valid
N (listwise)

150

 

 

 

Table 4.2.2 shows the descriptive analysis for privacy. The
variable have six mean score analysis for privacy that represent six
statements. Based on the table, the highest mean is 4.3364, with the statement
of “I am aware that users of the other social sites will
be notified if I post something on linked sites”. The score represents most of the respondents who were positively
agreed with the statement that they are aware that users of the other social sites will be notified if I post
something on linked sites. The lowest
mean is 2.0455, with the statement of “I always leave my personal information open to the
public on sites like Facebook”.

 

 

                                                                             

 

 

Table 4.2.3: Motivations to Share

 

 

N

Mean

Std. Deviation

 

By sharing through Social Media, I can
establish connections

110

4.4636

.71263

 

I need to share online in order to stay connected with other users around the
globe.

110

3.0545

1.14808

 

I define/delineate myself sharing content through Social Media

110

2.3182

1.03986

 

I felt that the content I shared is very
helpful to others.

110

3.1182

.80971

 

I always keep my content understandable by
others before they can share it to their circle.

110

4.3636

.65982

 

Having more virtual friends is far more
favorable than those in reality.

110

2.0273

1.05325

 

Valid
N (listwise)

150

 

 

 

 

Table 4.2.3 shows the descriptive
analysis for motivations to share. The variable have six mean score analysis
for motivations to share that represent six statements. Based on the table, the
highest mean is 4.4636, with the statement of “By sharing through Social Media, I can establish
connections”. The score
represents most of the respondents who were positively agreed with the
statement that by sharing through social media, they can build up connections.
The lowest mean is 2.0273 where the statement is about “Having more virtual friends is far more favorable than
those in reality”.

 

 

 

 

 

 

 

Table 4.2.4:
Security

 

 

N

Mean

Std. Deviation

 

My information is still vulnerable to identity
thieves even with the highest security level set.

110

4.2091

.73066

 

I am aware that whatever I put on my social media is
accessible by hackers to commit crimes.

110

4.3000

.97256

 

Sensitive personal detail is a good idea to be used
as password when signing up to social sites as it creates a strong and secure
password.

110

1.5818

.64084

 

Whenever I feel secured, I tend to share even more information with others.

110

3.9818

1.04031

 

I am aware that I can change the visibility
of my shared information to my contacts only.

110

4.0091

.98144

 

I have installed/updated the Anti-Virus software
system to prevent any unwanted scams & spams from showing up on my
screen.

110

3.2818

1.47226

 

Using an open network Wi-Fi is safe for me.

110

1.8909

.89181

 

I always used the same password for all social
sites.

110

2.6636

1.21366

 

I often change my password when I had used it for a
long time.

110

2.5091

1.23960

 

Valid
N (listwise)

150

 

 

 

 

Table 4.2.4 shows the descriptive
analysis for security. The variable have nine mean score analysis for security
that represent nine statements. Based on the table, the highest mean is 4.3000,
with the statement of “I am aware that whatever I put on my social media is accessible by
hackers to commit crimes”. The score
represents most of the respondents who were positively agreed with the
statement that they are aware that their posts are accessible by hackers. The
lowest mean is 2.0273 where the statement is about “Sensitive personal detail is a good idea to be used as
password when signing up to social sites as it creates a strong and secure
password”.

 

4.3 RELIABILITY ANALYSIS

Reliability analysis is used to measure the consistency and
stability of the variable. The Cronbach’s Alpha is a reliability coefficient
that show how well the items in a set which are positively correlated to one
other. Reliability less than 0.6 is poor, range from 0.6 to 0.8 is acceptable
and those over 0.8 are considered good.

Table 4.3.1: Internal consistency

Value

Description

< 0.6 Poor 0.6 < x < 0.8 Acceptable > 0.8

Good

Table 4.3.2: Reliability Analysis

No.
of Item

Variable

Cronbach
Alpha

Relationship

7

Social Media Risks Through
Information Sharing (DV)

0.646

Acceptable

6

Privacy (IV 1)

0.663

Acceptable

6

Motivations to share ( IV 2)

0.658

Acceptable

9

Security (IV 3)

0.666

Acceptable

Average
Cronbach’s Alpha score for all variables = 0.658 (Acceptable)

The table above indicates the Cronbach’s Alpha. From the table
above, the Cronbach’s Alpha range from .646 until .666. Regarding to this
table, all variables are reliable because all the Cronbach’s Alpha for these
variable are above than 0.6. The independent variables consist of 7, 6, 6 and 9
items respectively. Cronbach’s Alpha for social media risks, privacy,
motivations to share and security are .646, .663, .658 and .666 respectively. The
average score for all the variables is 0.658, which indicate that the
reliability for all variables is acceptable.

 

4.4 PEARSON’S
CORRELATION ANALYSIS

Person’s correlation coefficient is being done in order to show the
relationship between the independent variables and dependent variable.

 

Table 4.4.1: Pearson Correlation Coefficient range and strength

R

Strength
of Relationship

0
to 0.30
0 to -0.30

Positive
Weak Correlation
Negative Weak Correlation

0.30
to 0.70
-0.30 to -0.70

Positive
Moderate Correlation
Negative Moderate Correlation

0.70
to 1
-0.70 to -1

Positive
Strong Correlation/Positive Relationship
Negative Strong Correlation/Negative Realtionship

 

Table 4.4.2: Pearson’s Correlation Coefficient

Correlations

 

Social Media Risks

Privacy

Motivations To Share

Security

Social Media Risks

Pearson Correlation

1

 

 

 

Sig. (2-tailed)

 

 

 

 

N

110

 

 

 

Privacy

Pearson Correlation

.331**

1

 

 

Sig. (2-tailed)

.000

 

 

 

N

110

110

 

 

Motivations To Share

Pearson Correlation

.297**

.564**

1

 

Sig. (2-tailed)

.002

.000

 

 

N

110

110

110

 

Security

Pearson Correlation

.111

.045

.154

1

Sig. (2-tailed)

.248

.641

.109

 

N

110

110

110

110

**. Correlation is significant at the 0.01 level
(2-tailed).

Results of the correlation analysis are presented in Table 4.4.2.
The correlation table describes inter-correlation between three variables.
Based on the finding, the social media risks is correlated positively with all
independent variables which is privacy (r=.331, p<.01), motivations to share (r=.297, p<.01), and security (r=.111, p>0.1). Only one variable have a
positive moderate correlation, which is the privacy, while the other two have a
rather positive weak correlation, which is the motivations to share and
security.

The privacy is the best predictor to measure the factor that influences
the social media risks through information sharing. It is then followed by
motivations to share as the second best predictor, while security as the last
predictor to measure the factor that influences the social media risks through
information sharing.

The positive correlation indicates that the privacy, motivations to
share and security are good predictors to measure the factor that influences
the social media risks through information sharing. The result of the
correlation analysis provides initial support of study.

 

 

 

 

 

 

 

 

4.5 MULTIPLE
REGRESSIONS

Table 4.5.1: Multiple Regressions

Variables

?

Sig.

Constant

 

.000

Privacy

.245

.028

Motivations to share

.147

.188

Security

.077

.400

Adjusted R Square

.109

 

R Square

.133

 

F Test

5.434

.002

Result of multiple regressions was expressed in table 4.5.1. There
are three independent variables which are privacy, motivations to share and
security. The R square shows 0.133 that indicate 13.3% of the variance in the
independent variables can explain the dependent variable, where 86.7% of the
variance in the dependent variable cannot be explained by the independent
variables in the study.

The F Test shows the 5.434 (p < .05) which indicates that the model is significant base on the value of 0.002. Hence all independent variables significantly explained dependent variables. Based on the value of Beta, it is shown that privacy has the highest impact to the social media risks through information sharing. The variable for privacy is significant, because the p-value for it is 0.028 (2.8%), which is lower than 5% significant level. Hence, it is explained that privacy is significant related with the dependent variable. The variable for motivations to share is not significant. It is because the p-value for motivations to share is 0.188 (18.8%) which is above 5% significant level. Hence, it can be explained that motivations to share is not significantly related with dependent variable. The variable for security is not significant. It is because the p-value for security is 0.400 (40.0%) which is above than 5% significant level. Hence, it can be explained that security is not significant related with dependent variable. Based on the result, the equation of unstandardized beta coefficients is social media risks=3.008 + privacy=0.144 + motivations to share=0.100 + security=0.054. For every one-unit increase in privacy, the social media risks will experience an additional increase of 0.144 units. For every one-unit increase in motivations to share, the social media risks will experience an additional increase of 0.100 units. For every one-unit increase in security, the social media risks will experience an additional increase of 0.054 units. Based on the result, privacy (?=0.245, p<0.05) is a significant predictor to the dependent variable. The motivations to share shows that (?=0.147, p>0.05) it is not a significant predictor to the dependent
variable. The third variable which is security shows that (?=0.077, p>0.05)
indicate that it is not a significant predictor to the dependent variable.

The positive beta (+?) value described the strength of relationship
between privacy and the social media risks. Hence, the objective for privacy is
accepted.

The hypothesis can only be accepted if the significant value is
lower than 0.05 and will be rejected if the significant value is higher than
that. Based on this research, the significant values for all independent which
is privacy, motivations to share and security are 0.028, 0.188 and 0.400
respectively. This shows that the objective for privacy is accepted, while the
objectives for the other two variables are rejected.

 

 

 

 

 

 

 

 

4.6 RESULT HYPOTHESIS

H0 = no relationship
between the privacy and the social media risks through information sharing.
H1 = a
relationship between the privacy and
the social media risks through information sharing.

Hypothesis 1 is about the privacy. Based on the result in
correlation analysis, it shows (r = 0.331, p<0.01) has a positive moderate correlation for privacy. For hypothesis 1, H1 is accepted because the result shows that there is a relationship between privacy and the social media risks through information sharing. H0 = no relationship between the motivations and the social media risks through information sharing. H2 = a relationship between the motivations and the social media risks through information sharing. Hypothesis 2 is about the motivations to share. Based on the result in correlation analysis, it shows (r = 0.297, p<0.01) has a positive weak correlation for motivations. For hypothesis 2, H2 is accepted because the result shows that there is a relationship between motivations to share and the social media risks through information sharing. H0 = no relationship between security and social media risks through information sharing. H3    = a relationship between security and social media risks through information sharing. Hypothesis 3 is about security. Based on the result in correlation analysis, it shows (r = 0.111, p>0.01) has a positive weak correlation for
motivations. For hypothesis, H0 is accepted because the result shows that there is no relationship between motivations to share and the social media risks
through information sharing.

 

 

 

 

4.7 RESULT OF
OBJECTIVES

Table 4.7.1: Coefficient

Coefficientsa

Model

Unstandardized
Coefficients

Standardized
Coefficients

t

Sig.

Collinearity
Statistics

B

Std.
Error

Beta

Tolerance

VIF

1

(Constant)

3.008

.271

 

11.092

.000

 

 

PRIV

.144

.065

.245

2.232

.028

.680

1.471

MOTIV

.100

.076

.147

1.325

.188

.665

1.504

SECUR

.054

.064

.077

.844

.400

.974

1.027

a. Dependent Variable: SMR

Table 4.7.1 shows the coefficient for the
variables. It shows that privacy has a significant relationship with social
media risks as the significant level is <0.05 (0.0028). As for motivations to share, it shows that it has no significant relationship as the significant level is >0.05 (0.188). Lastly, the table shows that
security has no significant relationship with social media risks as the
significant level is >0.05 (0.400).

 

 

4.8 SUMMARY

Overall, this chapter is about running tests, which
include analysis and interpretation of the collected data. It is consists of
the interpretation on Reliability Test, Pearson’s Correlation Analysis and also
Multiple Regression.