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The structure of social collaboration on Wikipedia Sorin Adam Matei, Associate Professor of Communication, Purdue U smatei@purdue.edu David Braun, Research Scientist, Envision Lab, Purdue U dbraun@purdue.edu HoriaPetrache, Assistant Professor of Physics, IUPUI hpetrach@iupui.edu Presented at Wikimania, 2009 Buenos Aires, Argentina August 25-28 2009 http://wikimania2009.wikimedia.org/wiki/Proceedings:132
2005: A Wikipedian explains Wikipedia as Wisdom of Crowds The basic premise [of Wisdom of Crowds] that crowds of relatively ignorant individuals make better decisions than small groups of experts. I'm sure everyone here agrees with this as Wikipedia is run this way... Wikipedia displays emergent properties because each article is better than the contribution of each individual. Similarly, ants display emergence because an ant colony can accomplish things that each individual ant cannot even conceive.
Implied idea Fine grained, micro contributions, independent and decentralized and maybe equal lead to articles that are better than what each contributor can write
As expressed in this Wikipedia-l post I imagine Wikipedia as a massive, active swarm intelligence, supplemented by small roving groups of active editors who admire consistency, elegance, and reasoned discourse. (not unlike certain models of how the brain works :) The swarm does the bulk of the writing, especially finding and providing current facts, starting new articles, and adding neglected POVs. The roving groups are sensitive to dozens of policy pages, and implement them as they rove... they also take on large projects, one at a time, and try to implement certain changes across thousands of pages at once.
To which “Jimbo” (Wales) answers I should point out that I like Suroweicki'sthesis just fine, it's just that I'm not convinced that "swarm intelligence" is very helpful in understanding how Wikipedia works -- in fact, it might be an impediment, because it leads us away from thinking about how the community interacts in a process of reasoned discourse.
Jimbo concludes My research (conducted in December) showed that half the edits by logged in users belong to just 2.5% of logged in users.
Does the 80/20 applies? Power-law curves are all over the real world … Adar and Huberman (2000) found 50% of the content on Gnutella is provided by 1% of the users,  O'Mahonyand Ferraro (2003) found the curve in the Debian dev key ring, Moon and Sproul (2002) on the Linux Kernel list, Briggs et al. (1997) in group support systems, Krogh, Spaeth and Lakhani (2003) in Freenet. (By another participant to the 2005 discussion)
What would the 80/20 rule mean? Extreme inequality? Elitism? Structured collaboration? Interactive exchanges between groups of individuals?
Previous research Wikipedia contributions, in all languages, have become more skewed in favor of a small group of editors and old time users (Ortega et al., 2005)
Top contributors dominate edits and no words contributed
Our approach Increase in inequality => higher level of structuration Increasing division of labor From diffuse collaboration to structured collaboration Emergence of bureaucracy Emergence of adhocracy Groups of individuals that become article stewards
Social entropy and structuration Social Entropy As system become organized (biased) their entropy decreases Entropy is a measure of meaningful organization
Entropy and organization Meaningful messages use words and letters in uneven manner Symbol distribution in meaningful messages is uneven Information (and social) entropy are measures of organization and meaning As collaboration becomes more biased, the group becomes more organized
Shannon’s formula where the sum is over all users i, and is the fractional contribution of user i. We allow p and S  and to be functions of time (t).
Shannon’s forumal explained Social entropy reflects how uneven and lacking in diversity a group/system process is 10 users and 100 contributions,  each contributing 10 edits to a Wikipedia article =>  entropy reaches its highest level 1 contributor contributes all, entropy at the lowest value
Analytic strategy Downloaded latest available dump Trouble with unzipping (dump corrupted) Extracted  792,654 registered users 234,798 articles Calculated number of times individuals contributed to each article and how many words have they contributed (not completely finalized)
[object Object]
Orange: fit curve (takes into account the spread of values
Dotted: Maximum entropy, wisdom of crowds ceilingln(x) Intervention entropy Basic plot: Entropy increases for the first @500 interventions, then levels off…. Intervention number (events)
[object Object]

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Wikipedia structure of collaboration

  • 1. The structure of social collaboration on Wikipedia Sorin Adam Matei, Associate Professor of Communication, Purdue U smatei@purdue.edu David Braun, Research Scientist, Envision Lab, Purdue U dbraun@purdue.edu HoriaPetrache, Assistant Professor of Physics, IUPUI hpetrach@iupui.edu Presented at Wikimania, 2009 Buenos Aires, Argentina August 25-28 2009 http://wikimania2009.wikimedia.org/wiki/Proceedings:132
  • 2. 2005: A Wikipedian explains Wikipedia as Wisdom of Crowds The basic premise [of Wisdom of Crowds] that crowds of relatively ignorant individuals make better decisions than small groups of experts. I'm sure everyone here agrees with this as Wikipedia is run this way... Wikipedia displays emergent properties because each article is better than the contribution of each individual. Similarly, ants display emergence because an ant colony can accomplish things that each individual ant cannot even conceive.
  • 3. Implied idea Fine grained, micro contributions, independent and decentralized and maybe equal lead to articles that are better than what each contributor can write
  • 4. As expressed in this Wikipedia-l post I imagine Wikipedia as a massive, active swarm intelligence, supplemented by small roving groups of active editors who admire consistency, elegance, and reasoned discourse. (not unlike certain models of how the brain works :) The swarm does the bulk of the writing, especially finding and providing current facts, starting new articles, and adding neglected POVs. The roving groups are sensitive to dozens of policy pages, and implement them as they rove... they also take on large projects, one at a time, and try to implement certain changes across thousands of pages at once.
  • 5. To which “Jimbo” (Wales) answers I should point out that I like Suroweicki'sthesis just fine, it's just that I'm not convinced that "swarm intelligence" is very helpful in understanding how Wikipedia works -- in fact, it might be an impediment, because it leads us away from thinking about how the community interacts in a process of reasoned discourse.
  • 6. Jimbo concludes My research (conducted in December) showed that half the edits by logged in users belong to just 2.5% of logged in users.
  • 7. Does the 80/20 applies? Power-law curves are all over the real world … Adar and Huberman (2000) found 50% of the content on Gnutella is provided by 1% of the users, O'Mahonyand Ferraro (2003) found the curve in the Debian dev key ring, Moon and Sproul (2002) on the Linux Kernel list, Briggs et al. (1997) in group support systems, Krogh, Spaeth and Lakhani (2003) in Freenet. (By another participant to the 2005 discussion)
  • 8. What would the 80/20 rule mean? Extreme inequality? Elitism? Structured collaboration? Interactive exchanges between groups of individuals?
  • 9. Previous research Wikipedia contributions, in all languages, have become more skewed in favor of a small group of editors and old time users (Ortega et al., 2005)
  • 10. Top contributors dominate edits and no words contributed
  • 11. Our approach Increase in inequality => higher level of structuration Increasing division of labor From diffuse collaboration to structured collaboration Emergence of bureaucracy Emergence of adhocracy Groups of individuals that become article stewards
  • 12. Social entropy and structuration Social Entropy As system become organized (biased) their entropy decreases Entropy is a measure of meaningful organization
  • 13. Entropy and organization Meaningful messages use words and letters in uneven manner Symbol distribution in meaningful messages is uneven Information (and social) entropy are measures of organization and meaning As collaboration becomes more biased, the group becomes more organized
  • 14. Shannon’s formula where the sum is over all users i, and is the fractional contribution of user i. We allow p and S and to be functions of time (t).
  • 15. Shannon’s forumal explained Social entropy reflects how uneven and lacking in diversity a group/system process is 10 users and 100 contributions, each contributing 10 edits to a Wikipedia article => entropy reaches its highest level 1 contributor contributes all, entropy at the lowest value
  • 16. Analytic strategy Downloaded latest available dump Trouble with unzipping (dump corrupted) Extracted 792,654 registered users 234,798 articles Calculated number of times individuals contributed to each article and how many words have they contributed (not completely finalized)
  • 17.
  • 18. Orange: fit curve (takes into account the spread of values
  • 19. Dotted: Maximum entropy, wisdom of crowds ceilingln(x) Intervention entropy Basic plot: Entropy increases for the first @500 interventions, then levels off…. Intervention number (events)
  • 20.
  • 21. Orange: fit curve (takes into account the spread of values
  • 22. Dotted: Maximum entropy, wisdom of crowds ceilingln(x) Intervention entropy Intervention number (events) Logged plot: Average article entropy increasingly and monotonously diverges from the “wisdom of the crowds” ceiling. Wikipedia becomes “cooler” and more and more structured ….
  • 23. Standard deviation/ Int. Entropy After the 500th intervention the coefficient of variation (StDev/Mean) becomes constant; all articles tend to behave within the same limits of variability for the next 9,500 iterations n-1/2 ratio Intervention number (events)
  • 24. What remains to be done Entropy decreases, Wikipedia “hardens” Does it become more structured? In what way? Will analyze degree of structuration measuring structure of coedits (network) analysis Expectation: as entropy decreases, network structures become more hierarchical can inflexible (less degrees of freedom) Will analyze distribution of collaboration across formal and informal roles Who are the nodes of collaboration What is their contribution to cooling and hardening Wikipedia