1 / 33

The ties that bind: Social network principles in online communities.

The ties that bind: Social network principles in online communities. Alan Fco . Diaz Hernandez Prof. Dr. Eduard Heindl. Content. First part -Keywords -Introduction -Background -Network theory and social capital. Second part -Slashdot -Model and hypothesis -User conduct

inez
Download Presentation

The ties that bind: Social network principles in online communities.

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The ties that bind: Social network principles in online communities. Alan Fco. Diaz Hernandez Prof. Dr. Eduard Heindl

  2. Content First part -Keywords -Introduction -Background -Network theory and social capital Second part -Slashdot -Model and hypothesis -User conduct -Hypothesis 1,2,3,4 -Research design and data -Results -Conclusions

  3. Whatis a SOCIAL NETWORK?

  4. Keywords. • Online communities. • Social Capital. • Structural Holes. • Reputation Systems . • Web 2.0 • Ronald Stuart Burt

  5. Introduction. • Web 2.0 (Wikipedia, Facebook, Slashdot). • The clientis faceless. • Online socialnetworkshadbecome a parallel worldtomanypeople.

  6. Social network theory's. Online social networks. Brokerage Closure.

  7. Background. Can a online social networkwhich is not much more than a network be considered an organization? Aristoteles. Granovetter. Ouchi.

  8. Network theory and social capital. • Social Network  Social capital • Online Social networks. ex. TWITTER

  9. Network Theory. • Burt  Theory of social capital in network by focusing on the presence or absence of structural holes. • BROKERAGE vs. CLOSURE

  10. CLOSURE vs. BROKERAGE.

  11. Studies (Brokerage). • Burt The social capital of French and American managers. • Zaheery bell  Benefiting from network position: firm capabilities, structural holes, and performance.

  12. Studies (Closure). • Ashleight y Nandhakumar  Trust and technologies.

  13. So which one it´s better????

  14. Closure • Brokerage

  15. Second part Study for the site Slashdot.

  16. Site which provides news of technology founded in 1997. • How it works? • What´s “KARMA”. • 2002Online social network.

  17. Model and hypotheses • The relationship between network structure and social capital. Social capital  KARMA • Brokerage  High between ness/low constraint. • Closure  Low between ness/High constraint.

  18. Users conduct • Constraint • Between-ness

  19. Research design and data. • 6000 users with over 200,000 relationships. • Standard regression of several variables like: comments, friend ratio, foe ratio and karma. • Using UCINET.

  20. Results.

  21. Results. • Respond Hypothesis 1.

  22. Results. • Respond Hypothesis 2.

  23. Results. • Respond Hypothesis 3.

  24. Results. • Respond Hypothesis 4.

  25. Conclusion • Structural Holes have an important role in a social network. • Brokerage  lower levels of karma. • Closure  higher levels of karma. • Based on advertising.

  26. Conclusion High Karma Lower Karma

  27. Questions?

  28. Results

  29. How is karma generated?.

  30. Hypothesis 1. A.-Most participants of the site will exhibit both low between-ness and low constraint. B.-There will be more participants with high constraint measures than with high between-ness measures. C.-There will be few individuals who score highly in both constraint and between-ness.

  31. Hypothesis 2. A.-High between-ness and high constraint are individually associated with high social capital. B.-High between-ness and high constraint are jointly associated with high social capital. C.-High constraint is more associated with high social capital than is high between-ness.

  32. Hypothesis 3. A.-Between-ness is inversely related to participation intensity. B.-Constraint is directly related to participation intensity. C.-Network investment moderates the relationship between both between-ness and constraint and social capital.

  33. Hypothesis 4. A.-Positive outcomes from between-ness are more significant to those with high social capital. B.-Positive outcomes from constraint are more significant to those with low social capital.

More Related