Too Lazy to Read the Paper

David Lazer - The Extremely Early Mover

Sune Lehmann Season 2 Episode 10

I am super excited to have David Lazer (1,2) on the pod today. 

David Lazer needs no introduction. But here at lazypod we’re polite, so he get’s one anyway.

David Lazer is a University Distinguished Professor of Political Science and Computer Sciences, Northeastern University, and Co-Director, NULab for Texts, Maps, and Networks. Prior to coming to Northeastern University, he was on the faculty at the Harvard Kennedy School (1998-2009). In 2019, he was elected a fellow to the National Academy of Public Administration.

His research has been published in such journals as Science, Nature, Proceedings of the National Academy of Science, the American Political Science Review, Organization Science, and the Administrative Science Quarterly, and has received extensive coverage in the media, including the New York Times, NPR, the Washington Post, the Wall Street Journal, and CBS Evening News.

He is among the leading scholars in the world on misinformation and computational social science and has served in multiple leadership and editorial positions, including as a board member for the International Network of Social Network Analysts (INSNA), reviewing editor for Science, associate editor of Social Networks and Network Science, numerous other editorial boards and program committees.

As always we talk about David path through science, with a particular emphasis on Computational Social Science (3) - a field that he has been absolutely instrumental in establishing. But we also cover many other topics in this wide-ranging converstation which ends up covering his paper “Product diffusion through on-demand information-seeking behaviour” (4) which is one of his favorite papers and least cited, and which has a super-interesting backstory.

References
(1) https://lazerlab.net
(2) https://cssh.northeastern.edu/faculty/david-lazer/
(3) https://www.science.org/doi/10.1126/science.1167742
(4) https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0751