Speaking – Dean Eckles

Recent & Upcoming Speaking

2022.07.12
Long ties: Formation, social contagion, and economic outcomes.
Center for Humans and Machines, Max Planck Institute for Human Development.

2022.04.04
Long ties: Formation, social contagion, and economic outcomes.
Social, Behavioral and Experimental Economics seminar, Department of Economics / Ross School of Business / School of Information, University of Michigan.

2022.03.16
Long ties: Formation, social contagion, and economic outcomes.
Marketing seminar, Stanford University Graduate School of Business.

2022.01.26
Long ties: Formation, social contagion, and economic outcomes.
Marketing seminar, Kellogg School of Management, Northwestern University.

Selected talks with videos

Testimony before US Senate Subcommittee on on Communications, Media, and Broadband hearing on “Disrupting Dangerous Algorithms: Addressing the Harms of Persuasive Technology” (Video)

Long ties: Formation, social contagion, and economic outcomes.
Center for Humans and Machines, Max Planck Institute for Human Development.

Noise induced randomization in regression discontinuity designs.
Cornell Center for Applied Mathematics Colloquium.

Noise induced randomization in regression discontinuity designs, with discussion by Michal Kolesár.
Online Causal Inference Seminar.

Seeding with costly network information.
Simons Institute for the Theory of Computing, University of California, Berkeley.

When experiments are plentiful.
CODE@MIT 2016.

Panel on observational causal inference (with Eytan Bakshy, Guido Imbens & Eleanor Murray).
CODE@MIT 2019.

Estimating peer effects in networks with peer encouragement designs.
Applied Statistics seminar, Harvard IQSS.

Algorithmic transparency and assessing effects of algorithmic ranking.
Testimony before the US Senate Subcommittee on Communications, Media, and Broadband.
This addresses the questions: How does algorithmic ranking in social media work? How can we assess algorithmic impact & amplification? What can policy-makers do here?

Providing normative information increases intentions to accept a COVID-19 vaccine. Nature Communications.
When does sharing information about others’ behaviors cause more of that same behavior? This is both a central question in the social sciences and also important for effecting preventative health behaviors, including vaccination. We use a randomized experiment embedded in the international survey on COVID-19 we conducted with Meta and JHU to address this, providing evidence that these descriptive norms increase intentions to get vaccinated.

Bias and high-dimensional adjustment in observational studies of peer effects. JASA.
Are observational studies informative about social contagion? We use a massive randomized experiment in Facebook News Feed to identify peer effects in link sharing and compare these results to those using only observational data. The richest models are able to recover the experimental “gold standard” peer effect, at least for the most popular classes of behavior.

Estimating peer effects in networks with peer encouragement designs. PNAS.
We employ a novel experimental design to modulate how many likes and comments are received by 49 million Facebook users, allowing us to estimate network effects in adoption and use of communication technologies.