Ecology of Online Communities: Difference between revisions

Revision as of 00:37, 1 August 2020

This page documents work related to the NSF Cyber-Human Systems award Modeling the Ecological Dynamics of Online Organizations (IIS-1910202, IIS-1908850).

The overarching goal of this work is to understand ecological dynamics between online communities. Our concept of ecological dynamics is taken from ecological science in biology and from research in organizational and community ecology in organizational sociology and communication. The grant proposal elaborates a series of quantitative projects that will by-and-large test whether general findings from biology and organizational studies will apply to online communities. But there are also lots of reasons (and some empirical results) that suggest that the story won't be so simple. So we're also interested in considering qualitative projects that will help us to anticipate and explain findings from the quantitative studies. This might mean understanding how relationships between related communities are experienced and mediated.

Three time series of three different online communities that are all engaged in discussion of Harry Potter. It is clear that activity in all three is closely related and seems to be driven by things like releases of movies and books. Our work will seek to dynamics of these kinds of relationships in detail

Links and Resources

Project Description on the NSF website (Page for NU; Page for UW)
Project description and references from NSF application
Software git repository
Project management (Internal)

Pages Research In Progress

People

Jeremy Foote (Purdue University)
Benjamin Mako Hill [PI]
Soyeon Hwang (Northwestern)
Charles Kiene (UW)
Aaron Shaw (Northwestern) [PI]
Nathan TeBlunthuis (UW)

Biographies of everyone working on the award on the People page in this wiki

Funding and Disclaimer

This material is based upon work supported by the National Science Foundation under Grant Number IIS-1908850.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Revision as of 00:37, 1 August 2020 (edit) Benjamin Mako Hill (talk \| contribs) (→‎Links and Resources) ← Older edit		Revision as of 00:37, 1 August 2020 (edit) (undo) Benjamin Mako Hill (talk \| contribs) No edit summary Newer edit →
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	This page documents work related to the NSF Cyber-Human Systems ~~grant [https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908850~~ Modeling the Ecological Dynamics of Online Organizations (~~official link)]~~, ~~[https://mako.cc/academic/nsf~~-~~ecology_proposal-2019.pdf (project description / proposal~~)].		This page documents work related to the NSF Cyber-Human Systems award '''Modeling the Ecological Dynamics of Online Organizations''' (IIS-1910202, IIS-1908850).

	The overarching goal of this work is to understand ''ecological dynamics'' between online communities. Our concept of ''ecological dynamics'' is taken from ecological science in biology and from research in organizational and community ecology in organizational sociology and communication. The grant proposal elaborates a series of quantitative projects that will by-and-large test whether general findings from biology and organizational studies will apply to online communities. But there are also lots of reasons (and some empirical results) that suggest that the story won't be so simple. So we're also interested in considering qualitative projects that will help us to anticipate and explain findings from the quantitative studies. This might mean understanding how relationships between related communities are experienced and mediated.		The overarching goal of this work is to understand ''ecological dynamics'' between online communities. Our concept of ''ecological dynamics'' is taken from ecological science in biology and from research in organizational and community ecology in organizational sociology and communication. The grant proposal elaborates a series of quantitative projects that will by-and-large test whether general findings from biology and organizational studies will apply to online communities. But there are also lots of reasons (and some empirical results) that suggest that the story won't be so simple. So we're also interested in considering qualitative projects that will help us to anticipate and explain findings from the quantitative studies. This might mean understanding how relationships between related communities are experienced and mediated.