Editing Dialogues/Underproduction

From CommunityData
Warning: You are not logged in. Your IP address will be publicly visible if you make any edits. If you log in or create an account, your edits will be attributed to your username, along with other benefits.

The edit can be undone. Please check the comparison below to verify that this is what you want to do, and then publish the changes below to finish undoing the edit.

Latest revision Your text
Line 1: Line 1:
== Science of Community Dialogue: Aligning Contributor Effort with Community Need ==
== Science of Community Dialogue Session #7: Aligning contributors and audiences ==
<!-- {{notice Please read the [[Virtual Event Code of Conduct]].}} -->
<!-- {{notice Please read the [[Virtual Event Code of Conduct]].}} -->


[[File:underproduction-concept_diagram.png|thumb|A schematic diagram that identifies (mis)alignment between quality and importance.]]
[[File:underproduction-concept_diagram.png|thumb|A schematic diagram that identifies (mis)alignment between quality and importance.]]


;What: Dialogue on '''Aligning Contributor Effort with Community Need''' in the [[Community Data Science Collective]]'s [[Science of Community Dialogue Series]]
;What: "Aligning contributors and audiences" in the [[Community Data Science Collective]]'s [[Science of Community Dialogue Series]]
;When: December 15, 2023 9:00am-3:00pm (with an optional dinner at 6:00pm on December 14)
;When: December 15, 2023 9:00am-3:30pm (with an optional dinner at 6:00pm on December 14)
;Where: [https://citp.princeton.edu/ Center for Information Technology Policy], 3rd Floor on [https://m.princeton.edu/default/map/index?filter=sherrerd%20hall&_recenter=true Sherrerd Hall], Princeton University, Princeton, New Jersey  
;Where: [https://citp.princeton.edu/ Center for Information Technology Policy], 3rd Floor on [https://m.princeton.edu/default/map/index?filter=sherrerd%20hall&_recenter=true Sherrerd Hall], Princeton University, Princeton, New Jersey  
;Who: Attendance at this event is by invitation only.
;Who: Attendance at this event is by invitation only.
;Organizers: [[Benjamin Mako Hill]], [https://communication.northwestern.edu/faculty/aaron-shaw.html Aaron Shaw], [https://kayleachampion.com/ Kaylea Champion]
;Hosts: [[Community Data Science Collective]] and [https://citp.princeton.edu/ Princeton University Center for Information Technology Policy]


Imagine if we lined up every piece of open source software in terms of how important it was. Now imagine that we also lined them up in terms of their quality or the share of developer attention given to each piece of software's upkeep. Wouldn't it be great if the two things were strongly aligned so that the most important stuff was also the highest quality? Research has shown that in the case of open source software and Wikipedia, this is frequently not the case.
Imagine if we lined up every piece of open source software in terms of how important it was. Now imagine that we also lined them up in terms of their quality or the share of developer attention given to each piece of software's upkeep. Wouldn't it be great if the two things were strongly aligned so that the most important stuff was also the highest quality? Research has shown that in the case of open source and Wikipedia, this is frequently not the case.


When they're functioning well, markets can work to "align" supply with demand through price changes. In many online communities, participants choose their tasks based on their own interests. As a result, information artifacts produced by online communities is often ''underproduced'' in the sense that their quality is much less than we might imagine, given their importance. This dialogue session will be devoted to exploring the dynamics behind underproduction—a d discussing how community managers can more effectively manage these processes.
When they're functioning well, markets can work to "align" supply with demand through changes in price. In communities where participants get to choose the tasks, things are more difficult. As a result, the kind of value produced by online communities is often ''underproduced'' in the sense that their quality is much less than we might imagine, given their importance.


This event is organized by the CDSC and hosted and supported by the Princeton Center for Information Technology Policy. It is paid for, in part, by a National Science Foundation grant (IIS-2045055) so that it will be held at no cost to attendees.
We'll be exploring the dynamics behind underproduction—and discussing the ways in which community managers can more effectively manage these processes—through several presentations of academic work and extensive dialog between an invited group of scholars and leaders of online communities. We expect to host between 20 and 30 people.


__TOC__
This event is organized by the CDSC and being hosted and supported by the Princeton Center for Information Technology Policy. It is paid for, in part, by a National Science Foundation grant so that it will be held at no cost to attendees.


== Event Details ==
A code of conduct will be shared with participants prior to the event. Discussions will be held under Chatham House Rule. Presentations will be recorded and shared publicly, though discussions will not.


Attendees will include an invited group of 20 leaders, practitioners, researchers, and funders from communities and industry. The agenda will include a small number of short research presentations to help frame our discussion but devote the majority of our time together to dialogue.
{{notice|This page will be updated with more detailed information as we get closer to the event.}}
 
Discussions will be held under Chatham House Rule. Any presentations will be recorded and shared publicly but discussions will not.


==What is the Science of Community Dialogue Series?==
==What is the Science of Community Dialogue Series?==
Line 31: Line 27:
==What is the CDSC?==
==What is the CDSC?==


The [[Community Data Science Collective]] (CDSC) is an interdisciplinary research group made of up of faculty and students at the University of Washington Department of Communication, the Northwestern University Department of Communication Studies, the Carleton College Computer Science Department, and the Purdue University School of Communication.
The Community Data Science Collective (CDSC) is an interdisciplinary research group made of up of faculty and students at the University of Washington Department of Communication, the Northwestern University Department of Communication Studies, the Carleton College Computer Science Department, and the Purdue University School of Communication.


== Learn more ==
== Learn more ==
Line 37: Line 33:
If you'd like to learn more or get future updates about the Science of Community Dialogues, please join the '''[https://communitydata.science/mailman3/postorius/lists/cdsc-dialogues.communitydata.science low volume announcement list].'''
If you'd like to learn more or get future updates about the Science of Community Dialogues, please join the '''[https://communitydata.science/mailman3/postorius/lists/cdsc-dialogues.communitydata.science low volume announcement list].'''


Feel free to contact [[Benjamin Mako Hill]] or one of the other organizers if you have any questions about the event.
Feel free to contact [[Benjamin Mako Hill]] if you any questions about the event.
 
== Financial Support ==
 
This work is being supported by the US National Science Foundation (award [https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045055 IIS-2045055]) and by Princeton Center for Information Technology Policy.
Please note that all contributions to CommunityData are considered to be released under the Attribution-Share Alike 3.0 Unported (see CommunityData:Copyrights for details). If you do not want your writing to be edited mercilessly and redistributed at will, then do not submit it here.
You are also promising us that you wrote this yourself, or copied it from a public domain or similar free resource. Do not submit copyrighted work without permission!

To protect the wiki against automated edit spam, we kindly ask you to solve the following CAPTCHA:

Cancel Editing help (opens in new window)