|Machine learning and natural language processing for humanitarian response: a view from the field
This event will take place on 17th October 2018 at 11:30am (10:30 GMT)
Knowledge Media Institute, Berrill Building, The Open University, Milton Keynes, United Kingdom, MK7 6AA
Drawing on real-life case studies from Nepal, Indonesia, and Kenya, I will provide an overview of how crowdsourced and social media data are used or ignored in humanitarian response and the challenges they pose for practitioners. Designed in order to respond to these challenges, I will present early stage software prototypes using the Crisis Event Extraction Service, an open-source web API that automatically classifies crowdsourced and social media data during crisis situations. The API provides annotations for crisis-related documents, event types and information categories to help speed and prioritize the delivery of humanitarian aid. Speaking as a practitioner, I will also propose avenues for impactful research and design to help increase the adoption of new tools and methods.
The webcast is open to 300 users
| download calendar file (e.g. for MS Outlook and iCal)|