Fw: [CrisisMappers] Introduction and Data Request - DSSG (Data Science for Social Good fellowship @ University of Chicago)
Chris R Albon
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From: Nathan Leiby <natha...@gmail.com>
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To: crisis...@googlegroups.com
Date: Wednesday, July 10, 2013 11:17:45 AM
Subject: [CrisisMappers] Introduction and Data Request - DSSG (Data Science for Social Good fellowship @ University of Chicago)
Hi CrisisMappers,
We’re a team of students working at the Eric & Wendy Schmidt Data Science for Social Good fellowship (at the University of Chicago). Our task is to use machine learning and natural language processing to improve Ushahidi's workflow. For example, we are interested in automatically labeling messages received in Ushahidi crowdmaps - suggesting categories, urgency, language, and other meta-information that will ease the job of volunteers and administrators.
Here's a bit more about the fellowship and our project in particular. We’re on Twitter and a have blog if you'd like to follow along more closely.
We’re reaching out for help with two questions:
1) We have a tight timeline (until late August), and our goal in this program is to make something immediately practical, so our ambition is to create a useful toolkit/library for Ushahidi rather than a paper or presentation. Our code will be open-sourced and we hope beneficial beyond this immediate project. We'd feel very fortunate to get some feedback on our tools from this community before the summer is out. Would anyone like to be involved in this hands-on feedback process, in late July and early August? (No technical skills necessary.)
2) We'd also like to send a specific ask: do you have data from your own Ushahidi instance that you'd be willing to share, that we can use to train our machine learning algorithms? We have about 20 datasets, in various languages and from various events (election, natural disaster, etc). However, more data will help us improve our machine learning algorithms, so our tools are the best they can be. A CSV dump of reports would be useful, but an SQL dump of the deployment would be ideal since we are interested in making suggestions based on the original messages (SMS, emails, and tweets) before they have been labeled. Please do let us know if you can share your datasets with us.
We look forward to learning from your community and would be very interested in participating as volunteers. (I personally also am excited to hear more about the progress of the http://internet-response-league.com/.) --
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Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Mining large amounts of structured and unstructured data to identify patterns can help an organization rein in costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.