What should the ideal online community be?


Attraction-selection-attrition theory of online community size and resilience

The role that online discussion communities played in the development of relationships and the transfer of information within and across organization is fairly important and increasingly draw attention from both researchers and companies, especially during the current WEB 3.0 era, web-based computer mediated technology greatly facilitate online communication efficiency by providing infrastructures through which group-based communication can occur.Merchandiser and companies want to improve the underlying technologies of online communities with the purpose of enhancing the user satisfaction, but in practical, what decisions are they supposed to make to optimize the community?

The research conducted by Butler et al. (2014) can partly answer this question. They offer a model of key latent constructs influenced by technology choices and possible causal paths by which they have dynamic effects on communities.

The paper describes two key community characteristics that are most likely relevant, number of members i.e. community size and membership who are willing to stay involved with the community though possible variability and change in the topics discussed i.e. community resilience.

In order to capture the progress of community, an Attraction-Selection-Attrition (ASA) theory was raised in this paper, from which two new concepts was introduced: participation costs (how much time and effort are required to engage with content provided in a community) and topic consistency cues (how strongly a community signals that topics that may appear in the future will be in accordance with what is has hosted in the past).

The methodology applied by this study is simulation theory-building strategy. Modeling the A-S-A procedures where community phenomena emerge from individual activities allows the paper to extend theories that provide only a partial explanation of discussion community dynamics. In the model, a platform and autonomous individuals together form an online community while platform is passive agent and individuals are active agents, thus their behaviors bring about community size and community resilience.

The model predicts four propositions:

  • Participation cost will be inversely associated with community size
  • Participation costs will be positively associated with community resilience.
  • The strength of topic consistency cues will be inversely associated with community size.
  • The relationship between topic consistency cues and community resilience is curvilinear. Community platforms with very low and very high topic consistency cues are associated with greater community resilience; platforms that signal moderate topic consistency cues are associated with lower community resilience.

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The paper also provides an inspiring discussion about how the relationship between interest focus and participation costs affect community sustainability (see the graph above). Reducing participation costs can change the behavior of individuals who are tangentially interested and have uncertain expectations. On the other hand, this can also significantly change the content and volume of discussion activity and thus the nature of a community. Such finding can also shed new light on social media phenomena, and the paper cite MySpace and Facebook as two examples to verify their findings, concluding that understanding how platforms mediate the relationship between potential benefits, the realized benefits and expected benefits is of great value.

Reference:

BUTLER, B. S., BATEMAN, P. J., GRAY, P. H. & DIAMANT, E. I. 2014. An Attraction-Selection-Attrition Theory of Online Community Size and Resilience. Mis Quarterly, 38, 699-728.

Butler, B. S. 2001. “Membership Size, Communication Activity, and Sustainability: The Internal Dynamics of Networked Social Structures,” Information Systems Research (12:4), pp. 346-362.

Bateman, P. J., Gray, P. H., and Butler, B. S. 2011. “The Impact of Community Commitment on Participation in Online Com- munities,” Information Systems Research (22:4), pp. 841-854.

Kuk, G. 2006. “Strategic Interaction and Knowledge Sharing in the Kde Developer Mailing List,” Management Science (57:7), pp. 1031-1042.

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