Design issues in collecting the data on Ego-Centered Social Networks on the Web (RC33-2004)

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    Design issues in collecting the data on Ego-Centered Social Networks on the Web (RC33-2004) - Presentation Transcript

    1. Design issues in collecting the data on Ego-Centered Social Networks on the Web Gašper Koren, Valentina Hlebec, Vasja Vehovar, and Katja Lozar Manfreda [Faculty of Social Sciences, University of Ljubljana] RC33 - Sixth International Conference on Social Science Methodology Amsterdam, the Netherlands, August 20 th 2004
    2. Presentation outline
      • Aim of the study
      • Collecting data on ego-centered social networks
      • Data collection
      • Results
      • Conclusions
      • Further research
      http://websm.org/
    3. Aim of the study
      • To test some relevant methodological issues for collecting data on complex issues with self-administered survey methods (Web Survey):
        • 1. Influence of graphical design
        • 2. Way of collecting data on repeating questions
      http://websm.org/
    4. EGO Vesna Gašper Tina Peter Mark Vasja Katja
    5. Network Generator
      • Emotional support ( Burt, 1984 )
      • One out of four types of social support ( Cohen and Wills, 1985 )
      “ From time to time, most people discuss important personal matters with other people, for instance if they have problems at work, at university, with partner or parents or other similar situations. Who are the people with whom you discuss personal matters that are important to you? “ http://websm.org/
    6. Data collection
      • July - October 2001
      • RIS – Research on Internet in Slovenia Web Survey
      • Over 14.000 respondents
      • 1009/631 respondents answerd on module about interpersonal relationships
      Survey I.
      • August - September 2003
      • Special Survey on Social Networks
      • 291/261 respondents
      Survey II. http://websm.org/
    7. Survey I. (2001)
      • 631 valid respondents
      • 4 different network generators (measuring 4 different types of social support), 1 graphical design
      • Ego should answer 11 questions for every listed alter (alter-vise questioning)
      • 2 different types of question instructions (question wording)
      http://websm.org/
    8. Survey II. (2003)
      • 261 valid respondents
      • 1 network generator, 3 different graphical designs ( 10 n.s. , 5 n.s. , 1 n.s. )
      • 2 ways of collecting data on alters
          • (alter-vise vs. variable-vise)
      • short (5) vs. long questionaire (11)
      http://websm.org/
    9. http://websm.org/    Network composition    Network size Substantive results    Time needed    Drop-out    Item-missing data    Non-valid responses Data quality Alter- vs. variable-vise ( Study 2 ) Number of alters ( Studies 1, 2 ) Instructions ( Study 1 ) Effect on results Name interpreter Name generator Web questionnaire design Data analysis
    10. Non-valid response I.
      • Non-valid responses:
        • Names in plural (»family«, »friends«, etc.),
        • suspicios fake names (for example, Jaka Racman and Pajo Patak – caracters from cartoons),
        • the same entry several times,
        • entries such as »/«,
        • more than one name in each space
      • Overall they are rare
      http://websm.org/
    11. Non-valid response II. http://websm.org/
    12. Non-valid response III. p=0.013 http://websm.org/
    13. Item missing data (5 q) (5 q) (11 q) (11 q) http://websm.org/
    14. Number of listed alters I. http://websm.org/
      • Survey I. (2001)
        • graphical design with 30 name spaces
        • varying instructions (long vs. short)
    15. Number of listed alters II. http://websm.org/
          • 30 name spaces | 10 name spaces
      • max 30 13
      • mean 6.4 4.66
    16. Number of listed alters III. http://websm.org/
          • 10 name spaces | 5 name spaces
      • max 13 14
      • mean 4.66 4.06
      • p = 0.1
    17. Number of listed alters IV. http://websm.org/
          • 5 name spaces | 1 name spaces
      • max 14 16
      • mean 4.06 3.15
      • p = 0.01
    18. Average number of completed name interpreters (Survey I.) http://websm.org/
    19. Average number of completed name interpreters (Survey II.) http://websm.org/
    20. Conclusions I.
      • Web data collection mode can be used for collecting ego-centered data, however one should be aware of all disadvantages of this data collection mode
      • Invalid response are rare (but they still exist!)
      • Item-missing data are on average around 10%, regardless the way of collecting the data
      http://websm.org/
    21. Conclusions II.
      • Graphical design is highly suggestive
      • Design with one name space per screen give the network size, which is closest to other survey modes (telephone, face-to-face)
      • On the other hand it has more invalid responses!
      http://websm.org/
    22. Further research
      • How-to r educe number of additional questions on alters (reducing the respondent burden) without reducing qualitiy of collected data
      • Time needed for each type of answering questionaitre (Alter-vise vs. Variable-vise)
      http://websm.org/
    23. University of Ljubljana Faculty of Social Sciences http://www.websm.org/ http://www.ris.org/ http://www.fdv.uni-lj.si/
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