Asking the World in Real-Time: A Randomized, Anonymous Approach to Gathering Spatiotemporal Sentiment Data


Tuesday, September 20, 2022, 12:00pm to 1:00pm


Virtual via Zoom

Presentation by Danielle Goldfarb


This talk will discuss the design principles, advantages, limitations, and applications of random domain intercept technology (RDIT). RDIT is an “asking” technology that leverages the Web’s architecture to collect randomized and anonymous spatiotemporal data on people’s opinions and behaviors. The approach was originally developed to address some of the biases associated with conventional surveys. The randomized approach results in the inclusion of those who are typically excluded or underrepresented in most sentiment datasets. Data collection is continuous and time-stamped, and contains latitude and longitude information. 

The original application of the technology was for pandemic monitoring during the H1N1 pandemic and the technology has now been applied to a range of US and global applications, including in monitored environments. Danielle’s talk will discuss a wide range of current academic and policy applications. These include measuring perceptions of military conflict escalation in Russia/Ukraine and China/Taiwan, Chinese sentiment towards the US, misinformation and disinformation, election prediction, economic monitoring, Russia-China relations, and real-time Ukrainian migration intentions. 

The above image provided courtesy of the Asia Pacific Foundation of Canada.


Speaker Bio 

Danielle is VP, Global Affairs, Economics and Public Policy at RIWI (Real-Time Interactive Worldwide Intelligence) and a Distinguished Fellow at the Asia Pacific Foundation of Canada. RIWI’s random domain intercept technology leverages the global Web architecture to rapidly, anonymously, and continuously capture randomized, global human sentiment and experience data. Danielle’s role at RIWI is to explore and collaborate on applications of the technology for foreign/domestic policy and economic questions. Danielle’s Tedx talk is about who is left out of datasets and the importance of inclusive data for prediction and policy making. She is developing a course at the University of Toronto’s Munk School of Global Affairs on the use of new data tools for global affairs and public policy. Danielle’s research expertise is in economic sentiment and behavior, global trade, emerging technologies, and the global digital economy. Danielle has held senior roles at economic policy think tanks including the Conference Board of Canada and the C.D. Howe Institute, and holds an M.Phil. in International Relations from Cambridge University and a B.Comm. in Honours Economics from McGill University.

Registration is required to attend. For registration information, see event details at the CGA website.