Hi all,
This week at the Applied Statistics workshop we will be welcoming Brendan Meade, a Professor of Earth and Planetary Sciences at Harvard University. He will be presenting work entitled "A View of Compressed Sensing and Neural Network Emulation in Physical Sciences." He is providing the figure below in lieu of an abstract.
We will meet in CGIS Knafel Room 354 at noon and lunch will be provided.
Best,
Pam
Title: A View of Compressed Sensing and Neural Network Emulation in Physical Sciences
Figure:
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Hi all,
This week at the Applied Statistics workshop we will be welcoming Joseph Jay Williams, a Research Fellow in the Vice Provost for Advances in Learning Research Group at Harvard University. He will be presenting work entitled "Perpetually enhancing human learning through dynamic, personalized, collaborative experimentation." Please find the abstract below and on the website.
We will meet in CGIS Knafel Room 354 at noon and lunch will be provided.
Best,
Pam
Title: Perpetually enhancing human learning through dynamic, personalized, collaborative experimentation
Abstract: There is a proliferation of websites and mobile apps for helping people learn new concepts (e.g. online courses), and learn how to change health habits and behavior (e.g. websites for reducing depression, apps for quitting smoking). How can we use data from real-world users to rapidly enhance and personalize these technologies? I show how we can build self-improving systems by reimagining randomized A/B experimentation as an engine for collaboration, dynamic enhancement, and personalization. I present a novel system that enhanced learning from math problems, through crowdsourcing explanations and automatically experimenting to discover the best. My second application boosted responses to an email campaign, by experimentally discovering how to personalize motivational messages to a user's activity level. These self-improving systems use experiments as a bridge between designers, social-behavioral scientists and researchers in statistical machine learning.
Hi all,
This week at the Applied Statistics workshop we will be welcoming Dean Eckles, an Assistant Professor of Marketing at the MIT Sloan School of Management. He will be presenting work entitled "Estimating Peer Effects in Networks with Peer Encouragement Designs." Please find the abstract below and on the website. The paper can be found at: http://www.pnas.org/content/113/27/7316.abstract
We will meet in CGIS Knafel Room 354 at noon and lunch will be provided.
Best,
Pam
Title: Estimating Peer Effects in Networks with Peer Encouragement Designs
(Dean Eckles, René Kizilcec, Eytan Bakshy)
Abstract: Peer effects, in which the behavior of an individual is affected by the behavior of their peers, are central to social science. Because peer effects are often confounded with homophily and common external causes, recent work has used randomized experiments to estimate effects of specific peer behaviors. These experiments have often relied on the experimenter being able to randomly modulate mechanisms by which peer behavior is transmitted to a focal individual. We describe experimental designs that instead randomly assign individuals’ peers to encouragements to behaviors that directly affect those individuals. We illustrate this method with a large peer encouragement design on Facebook for estimating the effects of receiving feedback from peers on posts shared by focal individuals. We find evidence for substantial effects of receiving marginal feedback on multiple behaviors, including giving feedback to others and continued posting. These findings provide experimental evidence for the role of behaviors directed at specific individuals in the adoption and continued use of communication technologies. In comparison, observational estimates differ substantially, both underestimating and overestimating effects, suggesting that researchers and policy makers should be cautious in relying on them. This provides evidence about the role of directed behaviors in the adoption and continued use of broadcast functionality.
Hi all,
This week at the Applied Statistics Workshop will be welcoming Michael Peress, Associate Professor of Political Science and Economics at SUNY-Stony Brook (and here at Harvard this year). He will be presenting work entitled "Does Newspaper Coverage Mediate the Economic Vote?" Please find the abstract below and on the website.<https://arxiv.org/abs/1210.0870>
We will meet in CGIS Knafel Room 354 at noon and lunch will be provided.
Best,
Pam
Title: Does Newspaper Coverage Mediate the Economic Vote?
Abstract: Do voters punish incumbent governments when economic performance is poor or when the media report that economic performance is poor? We draw on an original data set of over 2 million newspaper articles reporting on the economy in 32 newspapers in 16 developed democracies over 32 years. We develop procedures for coding newspaper sentiment on the economy and apply our results to study the role of the media in driving the economic vote. Our results indicate voters respond directly to unemployment, but respond to newspaper coverage of growth. Our results suggest that newspapers play an important role in mediating the economic vote.
