About the Series
The IDEAL workshop series brings in four experts on topics related to the foundations of data science to present their perspective and research on a common theme. Chicago area researchers with an interest in the foundations of data science. The series will be remote while our universities and local government advise avoiding non-essential meetings. The virtual format will have two talks before lunch, two talks after lunch, and an early evening panel discussion (where appropriate).
Many important dynamic processes are determined by an underlying network structure. Examples include the spread of epidemics, the dynamics of public opinions, the diffusion of information about social programs, and biological processes such as neural spike trains. Data about these processes is becoming increasingly available which has lead to a number of different research communities to tackle related questions independently. What is the source of a rumor? Will a given disease spread widely? Who is the key player? This workshop will cover some new tools being developed to address such questions. The workshop speakers are, , .
- 10:55-11:00: Opening Remarks
- 12:30-1:30: Lunch Break
- 3:00-4:00: Afternoon Break
- 4:00-5:00: Panel Discussion with the Speakers
Please use this Google form to pose questions for the Panel and the speakers.
Titles and Abstracts
As we reach the apex of the COVID-19 pandemic across the globe, a pressing question facing us all: can we, even partially, reopen the economy without risking the second wave? Towards that, we first need to understand if shutting down the economy helped. And if it did, is it possible to achieve similar gains in the war against the pandemic while partially opening up the economy? And if so, how does that translate into policy?
In order to induce farmers to adopt a new agricultural technology, we use predictions from the threshold model of diffusion to target information to key individuals within villages in Malawi. We combine social network data and model simulations to ex ante determine who is treated in our field experiment. We observe adoption decisions in 200 villages over 3 years. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low.