Web Page: http://swift.ushahidi.com/extend/ideas/
Mailing List: http://groups.google.com/group/swiftriver
Ushahidi, which means "testimony" in Swahili, is a website that was initially developed to map reports of violence in Kenya after the post-election fallout at the beginning of 2008. Ushahidi's roots are in the collaboration of Kenyan citizen journalists during a time of crisis. The website was used to map incidents of violence and peace efforts throughout the country based on reports submitted via the web and mobile phone. This initial deployment of Ushahidi had 45,000 users in Kenya, and was the catalyst for us realizing there was a need for a platform based on it, which could be use by others around the world. Since then we have grown from an ad hoc group of volunteers to a focused organization. The team is comprised of individuals with a wide span of experience ranging from human rights work to software development. We have also built a strong team of volunteer developers in primarily in Africa, but also Europe and the U.S.
ABOUT THE PROJECT
Swiftriver is a free and open source software platform that uses a combination of algorithms and crowdsourced interaction to validate and filter news. It is an open source effort by many contributing people and organizations including Meedan, Appfrica, GeoCommons and Ushahidi. User-generated content is becoming an increasingly important source of information during emergency events while traditional media continues to play a pivotal role in documenting events as they unfold. These trends are expected to continue well into the future. The challenge, then, becomes filtering this growing torrent of information. There is an apparent tradeoff between crowdsourcing (opening the floodgates) and validation (the filter). One of the strengths of crowdsourcing is the ability to collect a high volume of information from highly diverse channels like Twitter, email, news sites, blogs, and SMS. Swift acts as the verifying filter for these different channels and is possible precisely because of the volume of information available from these sources. The more information generated, the more the community interacts with it, and the easier it becomes to identify mutually trusted sources.
- A predictive tagger module to tag short text reports using NLP & Active Learning techniques. This module aims to tag the short text reports (SMS, Tweets, E-mail subject lines) aggregated by SwiftRiver or Ushahidi with suitable keywords using Natural Language Processing with Active Learning techniques. The predictive tagger will be built upon a proper-noun centric approach and utilizes the association between various keywords based on past reports to generate suitable tags for future reports.
- RiverID - Centralized authentication & Distributed reputation RiverID is part OpenID server for centralized authentication and part RESTful server for distributed reputation. RiverID is built upon Google's AppEngine for scalability; serving user attributes, weighted reputations, and social data to numerous instances of SwiftRiver, various RiverID widgets and mashups.
- Swiftriver Project Proposal for Swift Reverberations and SULSa Below is my application for GoSC working on both Swift reverberations and SULSa. I hope that my application along with my resume included in the "additional info" section will provide a good picture of my qualifications and personality. If you have any questions regarding my application, please feel free to email me at firstname.lastname@example.org.