2. 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. What is a SOCIAL NETWORK?

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

5.  Web 2.0 (Wikipedia, Facebook, Slashdot).  The client is faceless.  Online social networks had become a parallel world to many people.

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

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

8.  Social Network  Social capital  Online Social networks. ex. TWITTER

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

11.  Burt  The social capital of French and American managers.  Zaheer y bell  Benefiting from network position: firm capabilities, structural holes, and performance.

12.  Ashleight y Nandhakumar  Trust and technologies.

13. So which one it´s better????

14.  Closure  Brokerage

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

17.  The relationship between network structure and social capital. Social capital  KARMAKARMA  Brokerage  High between ness/low constraint.  Closure  Low between ness/High constraint.

18.  Constraint  Between-ness

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

21.  Respond Hypothesis 1.Hypothesis 1.

22.  Respond Hypothesis 2.Hypothesis 2.

23.  Respond Hypothesis 3.Hypothesis 3.

24.  Respond Hypothesis 4.Hypothesis 4.

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

26. High Karma Lower Karma

27. Questions?

30. 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. 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. 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. 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.