Here is how UNICEF Draws on IBM Analytics to Give a Voice to Youth in Africa.

We are in Uganda and somewhere else where, the U.S. Fund for UNICEF announced a collaboration with UNICEF Uganda on U-report.

The goal is to provide a free SMS-based reporting tool that allows Ugandan youth to communicate with their government and community leaders using their cell phones.

Connectikpeople may recall that, launched in 2011, U-report began as a grassroots text-messaging system that conducts weekly polls for youth to share observations/opinions and speak out on issues affecting their lives. To date, more than 240,000 young adults in Uganda have joined the program. In addition to responding to surveys, Connectikpeople has observed that, U-reporters send in ‘unsolicited’ text messages, hoping to be heard on topics ranging from health, education and

gender-based violence.

In October 2013, UNICEF receives an average of 170,000 text messages per month. Approximately 20,000 of these are unsolicited messages and initial analysis suggested that seven percent of these require immediate action from community leaders or the government.  

Since February 2013, U-report uses text analytics and machine learning technologies from IBM Research to help deal with the flood of information by automating the classification of messages. UNICEF Uganda and IBM Research deployed A-Class, a text classification system trained to understand the content of the text messages and analyzes the data much faster, and with much more accuracy.  

For example, in May 2013, messages on what was confirmed to be flooding in the Kasese district of Uganda were identified in real time, allowing accurate and official information to be sent to relief workers and other partners who were able to respond to the disaster quickly. 

Connectikpeople also observed that as part of its further adoption, A-Class has the potential to help UNICEF Uganda pinpoint issues that might not immediately get picked up among the thousands of incoming messages, as well

All 386 Members of Parliament in Uganda are now subscribed to U-report and through this system they receive SMS updates on reports pertaining to key issues in their districts.

The A-Class text classification model was developed by IBM Research using a combination of supervised machine learning, the latest advances in text mining and keyword matching. The objective of the model is to classify each incoming text message into one of 12 UNICEF message categories , this classification task is particularly challenging given the brevity and frequent misspellings in SMS text messages. 

Based on the success of the U-report program in Uganda, UNICEF has launched it in Zambia, Burundi and South Sudan, with a roll out expected in the Democratic Republic of Congo. The technology collaboration with IBM will also continue to explore how to automatically assign action status to messages, making the system portable in other countries and understanding how the system could be implemented in non-English environments. 

U-report relies on RapidSMS, an open source software framework that works with any cell phone on the market, enabling UNICEF to connect with communities using a low-cost and popular device. Results from U-report surveys are publicized via the Polls Results section of the web site, and messages classified by A-Class are captured in real-time and displayed on the National Pulse page, allowing the public to visualize what issues are trending within each district in Uganda. Reports are also shared with government officials via newsletters and national media channels to ensure decision makers have access to information regarding their districts.