With USAID and the Development Impact Lab at UC Berkeley, the CITRIS Data and Democracy Initiative is developing a new social media platform that directly engages citizens and communities from developing regions to collectively assess conditions, needs, and outcomes related to engineering innovations in humanitarian assistance, solar energy, democracy and governance, and global health.
In contrast to polls and surveys that are extremely valuable for analysts, CAFÉ is user-facing: the CAFÉ platform will provide direct, immediate visual feedback to participants, allowing them to instantly understand where they stand on key issues with respect to other participants and encourage open-ended / qualitative responses that can enhance interaction between users. Like a coffeehouse, we envision CAFÉ as a grassroots, user-friendly, self-organizing environment that allows the wisdom of crowds to identify, highlight, and display patterns, trends, and insights as they emerge. To facilitate interactions, CAFÉ will incorporate techniques from deliberative polling, collaborative filtering, and multidimensional visualization.
Opinion Space, a precursor to CAFÉ that focused on social innovation, has been used since 2010 by the U.S. State Department. Thousands of participants from around the world use it to organize, visualize, and analyze constructive suggestions on foreign policy:
"Opinion Space will harness the power of connection technologies to provide a unique forum for international dialogue. This is...an opportunity to extend our engagement beyond the halls of government directly to the people of the world." - U.S. Secretary of State Hillary Clinton 2010
An example of the Opinion Space interface is below, our goal is to design and create new interfaces and assessment tools, including those that don't rely on smartphones or the internet for use in remote communities:
http://opinion.berkeley.edu/afron
Recent Papers:
- Using a Social Media Platform to Explore How Social Media Can Enhance Primary and Secondary Learning. Sanjay Krishnan, Yuko Okubo, Kanji Uchino, and Ken Goldberg. Learning International Networks Consortium (LINC) 2013 Conference. MIT, Cambridge, MA. June
- [.pdf]
- Distributed Spectral Dimensionality Reduction for Visualizing Textual Data. Sanjay Krishnan and Ken Goldberg. International Conference on Machine Learning (ICML) Workshop on Spectral Learning Methods, Atlanta, GA, June 2013. [.pdf]
Available for download from: http://goldberg.berkeley.edu/pubs/
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