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Factor analysis of social networking services behaviour and some characteristics of its users

Factor analysis of social networking services behaviour and some characteristics of its users. Boris Popov*, Bojana Bodroža Faculty of Philosophy, Novi Sad. * boris.popov@unsff.ns.ac.yu. Social Networking Sites (SNS). The most popular SNS: Prevalence:

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Factor analysis of social networking services behaviour and some characteristics of its users

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  1. Factor analysis of social networking services behaviour and some characteristics of its users Boris Popov*, Bojana Bodroža Faculty of Philosophy, Novi Sad *boris.popov@unsff.ns.ac.yu

  2. 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).

  3. 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

  4. 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!

  5. 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.

  6. Sample - 105 users of the Social Networking Sites Table 2: Age descriptives Table 1: Gender structure Graph 1: Age distribution

  7. 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) ...

  8. Results

  9. 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 • 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%)

  10. I factor – SNS addiction Table 3: I factor items with factor loadings

  11. II factor – SNS socializing Table 4: II factor items with factor loadings

  12. III factor – Negative attitude towards SNS communication Table 5: III factor items with factor loadings

  13. IV factor – Flirty communication Table 6: IV factor items with factor loadings

  14. V factor – SNS profile as social self Table 7: V factor items with factor loadings

  15. Correlations among SNB factors ** significant at p< .01; * significant at p< .05

  16. Reliability of the SNB scale 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

  17. Differences among various SNS users Table 9: socio-demographic variables and differences in SN behaviour

  18. Differences among various SNS users (cont.)

  19. Conclusions

  20. 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 internet & SNS: can these services help users enrich their “off-line” social life? personality dimensions and SNS behaviour

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