factor analysis of social networking services behaviour and some characteristics of its users boris...
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Factor analysis of social networking services behaviour and some characteristics of its users
Boris Popov*, Bojana Bodroža
Faculty of Philosophy, Novi Sad
Social Networking Sites (SNS)
• The most popular SNS:
• Prevalence:– North America - over 90% college students use Facebook
(Ellison, Heino & Gibbs, 2006)– Serbia - among young people who use the internet
• 61% uses Facebook and • 37% uses MySpace (Strategic Marketing Research, 2008).
What are the Social Networkins Sites and how do they look?
- virtual space for communication and development of social relations
- “Profile” – personal page where users provide information about themselves
- Common elements on SNS profiles: Name – real or virtual (nickname) Basic socio-demographic and personal information Personal interests and hobbies Friends Photos Messages
Why are the Social Networking Services interesting for psychology?
- Identity construction:- lack of face-to-face contact- anonymity
- Self-presentation- Hidden self- Hopped-for possible self (Zhao, Grasmuck & Martin, 2008)
- SNS addiction
}→ Enables people to carefully craft their virtual identity!
The Research Aims
• to explore the latent structure of virtual behaviours on the Social Networking Sites,
• to determine the differences between groups of SNS users in their virtual behaviour relative to:
their socio-demographic characteristics and their usership status on the SNS.
Sample- 105 users of the Social Networking Sites
M F Missing All
35 69 1 105
33.3% 65.7% 1% 100%
Min Max AM SD N
18 42 26.8 4.93 105Table 1: Gender structure
Table 2: Age descriptives
Graph 1: Age distribution
Instruments & Variables
Social Networking Behaviour Scale (SNB, Popov & Bodroža, 2008)-73 items- Likert response format
Socio-demographic variables: gender, age, level of education, place of living...
Variables considering the use of Social Networking Services, e.g.:- How long do you use SNS (form less than 6 moths to more than 2 years)- How many hours per day do you spent on SNS? (from less than 1 hour to more than 5 hours)- The level of privacy of user’s profile (completely private, partly private, public) ...
Factor analysis of the SNB• principal component analysis with promax rotation• interpretability as a criteria for determination the number of factors• extracted 5 interpretable factors, which accounted for 41,6% of
total variance1. SNS addiction (19,8%)
2. SNS socializing (6,9%)
3. negative attitude towards SNS communication (6,3%)
4. flirty communication (4,9%)
5. SNS profile as social self (3,8%)
I factor – SNS addiction
Nr of
item
Item Loadings
70. I often delay my work because of chatting or sending messages via SNS.
.90
69. Some people from my surrounding have drawn attention to me that I use SNS too much.
.70
72. I have tried to reduce time spent on SNS several times, but I haven’t managed to do so.
.70
12. I usually spend more time on SNS than I planned. .69
Table 3: I factor items with factor loadings
II factor – SNS socializing
Nr of
item
Item Loadings
61. I'm always glad to meet in person someone I know from Internet. .90
14. I have initiated meeting with someone I met via SNS. .79
46. For me, Internet is just another way of meeting new and interesting people.
.72
20. By using Internet, I have met a person with whom I was or still am in close relationship.
.63
Table 4: II factor items with factor loadings
III factor – Negative attitude towards SNS communication
Nr of
item
Item Loadings
40. I consider SNS communication sterile and impersonal. .74
21. I have a feeling that people on SNS pretend to be different than they are.
.74
09. I feel that SNS communication is full of stereotypes and pretending. .72
47. Most people who use SNS are loiterers. .67
Table 5: III factor items with factor loadings
IV factor – Flirty communication
Nr of
item
Item Loadings
27. I like to flirt using SNS. .61
34. I have glozed some information about myself when communicate on SNS in order to win someone’s sympathy.
.59
44. I have got in contact with persons via SNS for sex. .56
Table 6: IV factor items with factor loadings
V factor – SNS profile as social self
Nr of
item
Item Loadings
16. I never miss to reply to any SNS message. .66
24. I carefully pick photos that I attach to my SNS profile. .62
26. I carefully look for who will be on my 'top friends' list. .57
Table 7: V factor items with factor loadings
Correlations among SNB factors
I II III IV V
I 1 .54** .08 .33** .34**
II 1 .02 .36** .23*
III 1 .05 .08
IV 1 .19*
V 1
** significant at p< .01; * significant at p< .05
Reliability of the SNB scale
Factor α
I SNS addiction .91
II SNS socializing .91
III Negative attitude towards SNS communication .77
IV Flirty communication .78
V SNS profile as social self .77
Table 8 : Reliability of the SNB factors
• reliability of the whole SNB scale (without items 49, 52, 57, 65, 71 which did not load any factor) is .92
Differences among various SNS users
SD variable SNS addiction
SNS socializing
Negative attitude
Flirt Profile as social self
SNS in use
(myspace/facebook)
t(95)=.70
p>.40
t(95)=4,51
p=.00
t(95)=.86
p>.10
t(95)=-.17
p>.80
t(95)=2.01
p<.05
Length of user status
F(103)=4.66
p<.01
F(103)=11.1
p=.00
F(103)=1.01
p>.30
F(103)=2.78
p<.05
F(103)=.18
p>.60
Hours per day use F(104)=21.4
p=.00
F(104)=8.66
p=.00
F(104)=.64
p>.50
F(104)=3.19
p<.05
F(104)=.85
p>.40
Table 9: socio-demographic variables and differences in SN behaviour
Differences among various SNS users (cont.)
SD variable SNS addiction
SNS socializing
Negative attitude
Flirt Profile as social self
Distance of virtual friends
F(104)=.13
p>.90
F(104)=1.22
p>.30
F(104)=.12
p>.90
F(104)=3.50
p<.05
F(104)=1.14
p>.30
Number of virtual friends
F(104)=1.70
p>.10
F(104)=3.14
p<.05
F(104)=.22
p>.80
F(104)=1.05
p>.30
F(104)=.63
p>.60
Age r(105)=.02
p>.80
r(105)=.05
p>.57
r(105)= -.10
p>.30
r(105)= -.06
p>.50
r(105)= -.22
p<.05
• social networking behaviour is multidimensional construct• SNB - instrument with interpretable 5-factor structure• there are significantly different patterns of behaviour among various
SNS users
further researches:
clusters of SNS users
personality dimensions and SNS behaviour
internet & SNS: can these services help users enrich
their “off-line” social life?