RadioSilenced: A Semi-Serendipitous Hyper Local Talk Radio Exploration Tool

Maggie Hughes

Nov. 15, 2019


Margaret A. Hughes, Deb Roy. 2019. RadioSilenced: A Semi-Serendipitous Hyper Local Talk Radio Exploration Tool. In Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing (CSCW ’19). Association for Computing Machinery, New York, NY, USA, 221–225. DOI:


In this poster, we show the under heard voices of those whose primary media is radio, the proliferation of large trend analysis over fine-grained exploratory tools for large scale media data, and the absence of exploratory tools for hyper local media like local radio. In response,  we present RadioSilenced, a web-based tool that enables the semi-serendipitous (not algorithmically curated) exploration and display of talk radio call-in data to encourage a deeper understanding of the 10 percent of US communities whose primary news consumption is radio, in a whole-system view but sample-by-sample exploration closer to ethnographic observation than a more reductive, big data analysis. To our knowledge, this is one of the first large scale analysis of ASR bias in talk radio, one of the oldest forms of media.

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