Hi all, The next Research Showcase will be live-streamed on Wednesday, January 20, at 9:30 AM PST/17:30 UTC. In this month’s showcase, Aaron Shaw will present ongoing research illustrating the values and challenges of macro-level organizational analysis of peer production and social computing systems. Specifically, he will give an overview on different studies showing convergent trends of formalization in large Wikipedias; divergent editor engagement in small Wikipedias; and commensal patterns of ecological interdependence across communities.
Youtube stream: https://www.youtube.com/watch?v=v9Wcc-TeaEY https://www.youtube.com/watch?v=ujd8S82YfmA
As usual, you can join the conversation on IRC at #wikimedia-research. You can also watch our past research showcases here: https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase*Speaker*: Aaron Shaw (Northwestern University) *Title*: The importance of thinking big. Convergence, divergence, and interdependence among wikis and peer production communities *Abstract*: Designing and governing collaborative, peer production communities can benefit from large-scale, macro-level thinking that focuses on communities as the units of analysis. For example, understanding how and why seemingly comparable communities may follow convergent, divergent, and/or interdependent patterns of behavior can inform more parsimonious theoretical and empirical insights as well as more effective strategic action. This talk gives a sneak peak at research-in-progress by members of the Community Data Science Collective http://communitydata.science/ to illustrate these points. In particular, I focus on studies of (1) convergent trends of formalization in several large Wikipedias; (2) divergent editor engagement among three small Wikipedias; and (3) commensal patterns of ecological interdependence across communities. Together, the studies underscore the value and challenges of macro-level organizational analysis of peer production and social computing systems.
Just a reminder, that this will be starting in about 24 minutes.
On Tue, Jan 19, 2021 at 6:01 PM Martin Gerlach mgerlach@wikimedia.org wrote:
Hi all, The next Research Showcase will be live-streamed on Wednesday, January 20, at 9:30 AM PST/17:30 UTC. In this month’s showcase, Aaron Shaw will present ongoing research illustrating the values and challenges of macro-level organizational analysis of peer production and social computing systems. Specifically, he will give an overview on different studies showing convergent trends of formalization in large Wikipedias; divergent editor engagement in small Wikipedias; and commensal patterns of ecological interdependence across communities.
Youtube stream: https://www.youtube.com/watch?v=v9Wcc-TeaEY https://www.youtube.com/watch?v=ujd8S82YfmA
As usual, you can join the conversation on IRC at #wikimedia-research. You can also watch our past research showcases here: https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase*Speaker*: Aaron Shaw (Northwestern University) *Title*: The importance of thinking big. Convergence, divergence, and interdependence among wikis and peer production communities *Abstract*: Designing and governing collaborative, peer production communities can benefit from large-scale, macro-level thinking that focuses on communities as the units of analysis. For example, understanding how and why seemingly comparable communities may follow convergent, divergent, and/or interdependent patterns of behavior can inform more parsimonious theoretical and empirical insights as well as more effective strategic action. This talk gives a sneak peak at research-in-progress by members of the Community Data Science Collective http://communitydata.science/ to illustrate these points. In particular, I focus on studies of (1) convergent trends of formalization in several large Wikipedias; (2) divergent editor engagement among three small Wikipedias; and (3) commensal patterns of ecological interdependence across communities. Together, the studies underscore the value and challenges of macro-level organizational analysis of peer production and social computing systems.
-- Martin Gerlach Research Scientist Wikimedia Foundation