Networked communities are a form of technology- mediated environment that foster a sense of community among users. They often materialise through platforms, such as portals or large websites, enabling members’ participation and collaboration towards certain goals. As an instance of collective action, networked communities are dependent upon the sustainability of their underlying platform. Thus, platforms are only partially designed during initial setup. They are expected to expand and grow organically and through linkages to other websites, following advances in social media and collaborative APIs. In the course of use, such platforms ‘virtually’ connect data repositories from several sources, including social media, blogs, doodles, notepads, news pages, etc. Together, they record and trace members’ daily practices and interactions over time, gradually building a digital memory for their community.
To be able to access such a memory and inform how members perform their identity, define practices, interact and negotiate collective knowledge, researchers must build comprehensive research methodologies, combining quantitative and qualitative methods. Epistemologically, combining methods may raise concerns as to whether quantitative and qualitative assumptions can be integrated meaningfully and how this affects the overall study, in terms of scope, validity and ethics of research. In this regard, this abstract argues that big data can support and extend the scope of a qualitative exploration of networked communities through visualisation techniques, tables and data mining filters. This abstract illustrates such a ‘hybrid’ qualitative approach in the context of an open source (OS) networked community for microfinance NGOs.
The idea behind OS for microfinance is that powerful institutional actors including civil society, IT partners, consultants and sponsors can cater to the lack of software and IT competences among small microfinance grassroots in developing countries by organising their collective and sustained participation in OS development over time. This vision was exemplified in a case of platform-enabled OS-microfinance community, named Mifos, which I studied.
The Mifos case study posed a methodological challenge; to study it I had to re-assemble the ‘big forest’ picture of the Mifos networked community, by traversing back and fro such a macro structure over a period of 10 years of activity – that is by linking the Mifos OS code growth with the daily practices of its inhabitants reflected through their 20,000 posts in the community mailing lists. Visualisation in this case was crucial to describe the ‘stuff’ this community was made of. It provided a sense of community and togetherness in the measurable terms of density, materiality, divisions and scope. The visual outputs contributed in identifying certain meaningful data objects, and brought out changes and relevant patterns. Overall, the visualisation provided a framework for exploration that guided in the second stage of the analysis a longitudinal narrative of the Mifos biography and the documenting of some community-enabled mechanisms of knowledge sharing and building among its members.
References
Armendariz, D.A.B. & Morduch, J., 2005. The Economics of Microfinance, MIT Press; Cambridge, Mass.
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Mynatt, E.D. et al., 1997. Design for Network Communities. In Proceedings of the ACM SIGCHI Conference on Human factors in computing systems. CHI ’97. New York, NY, USA: ACM, pp. 210–217.
Ray, D., 2007. Development Economics. New York University Working papers; prepared for The New Palgrave Dictionary of Economics, edited by Lawrence Blume and Steven Durlauf
