Transcript Slide 1
Factor analysis of social networking services behaviour and some characteristics of its users Boris Popov*, Bojana Bodroža Faculty of Philosophy, Novi Sad *[email protected] 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 Table 2: Age descriptives Table 1: Gender structure M F Missing All 35 69 1 105 33.3% 65.7% 1% 100% Min Max AM SD N 18 42 26.8 4.93 105 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) ... Results 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 variance 1. 2. 3. 4. 5. SNS addiction (19,8%) SNS socializing (6,9%) negative attitude towards SNS communication (6,3%) flirty communication (4,9%) SNS profile as social self (3,8%) I factor – SNS addiction Table 3: I factor items with factor loadings 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 II factor – SNS socializing Table 4: II factor items with factor loadings 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 III factor – Negative attitude towards SNS communication Table 5: III factor items with factor loadings 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 IV factor – Flirty communication Table 6: IV factor items with factor loadings 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 V factor – SNS profile as social self Table 7: V factor items with factor loadings 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 Correlations among SNB factors I II I II III IV V 1 .54** .08 .33** .34** 1 .02 .36** .23* 1 .05 .08 1 .19* III IV V ** significant at p< .01; * significant at p< .05 1 Reliability of the SNB scale Table 8 : Reliability of the SNB factors 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 • 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 Table 9: socio-demographic variables and differences in SN behaviour SD variable SNS in use (myspace/facebook) SNS addiction SNS socializing Negative attitude Flirt Profile as social self 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 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 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 Age Conclusions • 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?