[FoME] Using machine learning to analyse radio talk on sustainable and humanitarian action

Christoph Dietz Christoph.Dietz at CAMECO.ORG
Do Feb 21 18:12:08 CET 2019

Using machine learning to analyse radio talk in Uganda: opportunities for sustainable development and humanitarian action
By John Quinn and Paula Hidalgo-Sanchis
UN Global Pulse; Pulse Lab Kampala, 2017, 23 p.

Download at https://undg.org/wp-content/uploads/2017/09/Using-machine-learning-radio-content-uganda.pdf

"This report outlines the methodology and processes of the Radio Content Analysis Tool, a prototype developed by Pulse Lab Kampala to analyse public radio content in Uganda and explore its value for informing development of UN projects and programmes on the ground. It distills the technology behind the creation of the Radio Content Analysis Tool and presents the lessons learned along the way. The report also details the results of several pilot studies that were conducted together with partners from the Government, UN agencies and academia to understand the validity and value of unfiltered public radio discussions for development ... By sampling different indigenous languages, types of broadcasters, and locations within Uganda, the pilot studies assess the potential uses of radio talk across five topics: perceptions towards refugees in Uganda, the impact of small-scale disasters on livelihoods, perceptions around the delivery of healthcare services, understanding the spread of infectious diseases, and monitoring the effectiveness of awareness raising radio campaigns." (executive summary)

Here is a selection of reports on this project:

Dr. Christoph Dietz
Postfach 10 21 04 
D-52021 Aachen, Germany
Tel.: 0049 - 241 - 70 13 12 14
Fax: 0049 - 241 - 70 13 12 33
christoph.dietz at cameco.org 

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