A Farm in Every Window: A Study into the Incentives for - - PowerPoint PPT Presentation

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A Farm in Every Window: A Study into the Incentives for - - PowerPoint PPT Presentation

A Farm in Every Window: A Study into the Incentives for Participation in the Window Farm Virtual Community Dominic DiFranzo Alvaro Graves Outline Introduction Window Farm Community Incentive/Participation Models Methodology


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A Farm in Every Window:

A Study into the Incentives for Participation in the Window Farm Virtual Community Dominic DiFranzo Alvaro Graves

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Outline

  • Introduction
  • Window Farm Community
  • Incentive/Participation Models
  • Methodology
  • Results
  • Future Work/Conclusion
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Introduction

  • Many virtual communities fail or die off

due to users not participating.

  • Need better understanding on the

motivations and incentives on contributing to virtual communities.

  • No unifying model or consensus on

incentives or incentivization in virtual communities and this makes studying them very difficult.

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Introduction

  • Our study looked into the incentive

structures for members of the Window Farm virtual community.

– Look and tie different models & methodologies from different disciplines – Propose a methodology to tie motivations reported by users to the activity they express in the community

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Window Farm

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Window Farm Community

  • Multi-blogging platform
  • R&D-I-Y (research and develop it

yourself)

  • 20,000 registered users
  • 2,000 visiting users in a month
  • 45-60 activity contributors in a month
  • About 10 users are responsible for over

80% of the content in a month

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Methodology

  • Used models and methodology from

different disciplines (see paper for more)

  • Two parts (survey & classification and

analysis of the behavior in the community)

  • Tied results from survey to classification
  • f behavior for particular users
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  • Survey

– 48 Responses – Asked questions about Motivations for different behavior and actions – Also asked questions on sense of community and activity levels

  • Behavior classification

– (Question, Answer, Sharing, Social) – Done by hand

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Results

  • Overall Motivations

– Self satisfaction and self-improvement – Learning new skills

  • Answering and Sharing had two similar

Motivations (Fun to do, Obligation to community)

  • Answering had a different motivation

(Ideology)

  • Sharing differed also (Getting feedback
  • n ideas)
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Results

  • Neither the Fun or Obligation to

community motivation were positively correlated with answering questions or sharing ideas.

  • Ideology was positively was correlated

to answering questions.

  • Getting feedback on ideas was

correlated to sharing ideas.

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Future Work

  • These motivations tie well with Open

Source communities (best practices?)

  • Connect models better to develop better

unified understanding of motivation

  • Run experiments to test models and

features in communities.

  • Develop better methodology and

methods to explore this topic

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Questions?

  • Thanks to Britta Riley and Window

Farm Team

  • Send questions to difrad@rpi.edu
  • Twitter: @difrad