Proceedings of the Eighth International Conference on Information and Communication Technologies and Development 2016
DOI: 10.1145/2909609.2909670
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Design Lessons from Creating a Mobile-based Community Media Platform in Rural India

Abstract: Our research presents the case-study of a mobile phone based, voice-driven platform -Mobile Vaani (MV), established with a goal to empower poor and marginalized communities to create their own local media. In this paper, we derive a comprehensive theory of change for MV from the data gathered using the Most Significant Change technique. This paper contributes towards formulating a theory of change for technology-driven community media platforms which can be adapted to other ICTD interventions too.

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Cited by 56 publications
(26 citation statements)
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“…We saw that technology alone cannot bring change, it needs supporting pillars around it to nurture its use, guide the users, build services on top of the technology, create institutional linkages to run these services well, etc [3,31,32]. Once we started our own participatory media network, we had to quickly expand our team to bring in content specialists, community mobilization experience, and programme design, to support the technology so that it could support the users to use it meaningfully.…”
Section: Going Beyond Technologymentioning
confidence: 99%
See 1 more Smart Citation
“…We saw that technology alone cannot bring change, it needs supporting pillars around it to nurture its use, guide the users, build services on top of the technology, create institutional linkages to run these services well, etc [3,31,32]. Once we started our own participatory media network, we had to quickly expand our team to bring in content specialists, community mobilization experience, and programme design, to support the technology so that it could support the users to use it meaningfully.…”
Section: Going Beyond Technologymentioning
confidence: 99%
“…It was not only more costly to reach women users, or poorer families that rely on government schemes, but also their information needs seemed to be more complex than straightforward reporting of local news. We therefore faced a question of how much resources should we spend for this userbase that arguably needs our services more desperately but is more expensive to service [3,31,32]. Similarly, being able to support this marginalized userbase to get their rights and entitlements under different government schemes, and to improve the quality of public and private services availed by them, has brought us a lot of social credibility but it required additional effort and hence incurred an additional cost [4].…”
Section: A Context Of Impact Investing and A Market Driven Approachmentioning
confidence: 99%
“…There is a mature body of research surrounding IVR services in low-resource environments. Voicebased social platforms such as Polly [29], Baang [31], Mobile Vaani [23] and Sangeet Swara [38] have shown the ability to spread virally to a large number of users, including blind and visually impaired users [39]. Polly Health [43] is an example of how this viral spread can be leveraged to disseminate health information between peers.…”
Section: Related Workmentioning
confidence: 99%
“…Polly Health [43] is an example of how this viral spread can be leveraged to disseminate health information between peers. Voice forums in additional domains such as citizen journalism [21,23], agriculture [25], and maternal health [6] have shown strong usage and impact. Learn2Earn seeks to build upon the lessons learned in these projects.…”
Section: Related Workmentioning
confidence: 99%
“…Similarly, Avaaj Otalo [19] was used to broadcast agricultural community radio shows where the show producer would incorporate concerns shared through voice calls into the development of the show. Taking this further, Mobile Vaani allows listeners to comment on audio clips and share content with others [16] to sustain a dialogue within the community. However, there are few examples of IVR supporting health directly.…”
Section: Telephony In Resource Constrained Settingsmentioning
confidence: 99%