gov3009-l October 2018

gov3009-l@lists.fas.harvard.edu

1 participants
9 discussions

Applied Stats Workshop TOMORROW (Wed. 10/31) - Edward Kao and Steven Smith

by Connor Jerzak

*FINAL REMINDER --- Applied Statistics Workshop TOMORROW (10/31) at 12 noon* *Lunch provided --- All are welcome * ------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------ Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) tomorrow on Wednesday (10/31). The speakers are* Edward Kao *and* Steven Smith *(MIT Lincoln Laboratory) who will be presenting their work "Network Causal Inference on Social Media Influence Operations" (paper link <https://arxiv.org/abs/1804.04109>). *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 31st --- 12 noon - 1:30 pm. *Abstract:* Estimating influence on social media networks is an important practical and theoretical problem, especially because this new medium is widely exploited as a platform for disinformation and propaganda. This paper introduces a novel approach to influence estimation on social media networks and applies it to the real-world problem of characterizing active influence operations on Twitter during the 2017 French presidential elections. The new influence estimation approach attributes impact by accounting for narrative propagation over the network using a network causal inference framework applied to data arising from graph sampling and filtering. This causal framework infers the difference in outcome as a function of exposure, in contrast to existing approaches that attribute impact to activity volume or topological features, which do not explicitly measure nor necessarily indicate actual network influence. Cramer-Rao estimation bounds are derived for parameter estimation as a step in the causal analysis, and used to achieve geometrical insight on the causal inference problem. The ability to infer high causal influence is demonstrated on real-world social media accounts that are later independently confirmed to be either directly affiliated or correlated with foreign influence operations using evidence supplied by the U.S. Congress and journalistic reports. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 5 months

Applied Statistics Workshop Next Week (Wed. 10/31) - Edward Kao and Steven Smith

by Jerzak, Connor

Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) next week on Wednesday (10/31). The speakers are* Edward Kao *and* Steven Smith *(MIT Lincoln Laboratory) who will be presenting their work "Network Causal Inference on Social Media Influence Operations" (paper link <https://arxiv.org/abs/1804.04109>). *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 31st --- 12 noon - 1:30 pm. *Abstract:* Estimating influence on social media networks is an important practical and theoretical problem, especially because this new medium is widely exploited as a platform for disinformation and propaganda. This paper introduces a novel approach to influence estimation on social media networks and applies it to the real-world problem of characterizing active influence operations on Twitter during the 2017 French presidential elections. The new influence estimation approach attributes impact by accounting for narrative propagation over the network using a network causal inference framework applied to data arising from graph sampling and filtering. This causal framework infers the difference in outcome as a function of exposure, in contrast to existing approaches that attribute impact to activity volume or topological features, which do not explicitly measure nor necessarily indicate actual network influence. Cramer-Rao estimation bounds are derived for parameter estimation as a step in the causal analysis, and used to achieve geometrical insight on the causal inference problem. The ability to infer high causal influence is demonstrated on real-world social media accounts that are later independently confirmed to be either directly affiliated or correlated with foreign influence operations using evidence supplied by the U.S. Congress and journalistic reports. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop TOMORROW (Wed. 10/24) - Tyler VanderWeele

by Connor Jerzak

*FINAL REMINDER --- Applied Statistics Workshop TOMORROW (10/24) at 12 noon* *Lunch provided --- All are welcome * ------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------ Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) tomorrow on Wednesday (10/24). The speaker is* Tyler J. VanderWeele *(Harvard School of Public Health) who will be presenting his work "On the Promotion of Human Flourishing, with Methodological Reflections" (paper link 1 <http://www.pnas.org/content/pnas/114/31/8148.full.pdf>; paper link 2 <https://cdn1.sph.harvard.edu/wp-content/uploads/sites/603/2018/10/OutcomeWi…> ) *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 24th at 12 noon - 1:30 pm. *Abstract:* Many empirical studies throughout the social and biomedical sciences focus only on very narrow outcomes such as income, or a single specific disease state, or a measure of positive affect. Human well-being or flourishing, however, consists in a much broader range of states and outcomes, certainly including mental and physical health, but also encompassing happiness and life satisfaction, meaning and purpose, character and virtue, and close social relationships. The empirical literature from longitudinal, experimental, and quasiexperimental studies is reviewed in attempt to identify major determinants of human flourishing, broadly conceived. Measures of human flourishing are proposed. Discussion is given to the implications of a broader conception of human flourishing, and of the research reviewed, for policy, and for future research in the biomedical and social sciences. Discussion will also be given to the methodological implications of attempts to study numerous outcomes at once and to a proposed movement towards outcome-wide longitudinal designs for causal inference. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop Next Week (Wed. 10/24) - Tyler VanderWeele

by Connor Jerzak

Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) next week on Wednesday (10/24). The speaker is* Tyler J. VanderWeele *(Harvard School of Public Health) who will be presenting his work "On the Promotion of Human Flourishing, with Methodological Reflections" (paper link 1 <http://www.pnas.org/content/pnas/114/31/8148.full.pdf>; paper link 2 <https://cdn1.sph.harvard.edu/wp-content/uploads/sites/603/2018/10/OutcomeWi…> ) *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 24th at 12 noon - 1:30 pm. *Abstract:* Many empirical studies throughout the social and biomedical sciences focus only on very narrow outcomes such as income, or a single specific disease state, or a measure of positive affect. Human well-being or flourishing, however, consists in a much broader range of states and outcomes, certainly including mental and physical health, but also encompassing happiness and life satisfaction, meaning and purpose, character and virtue, and close social relationships. The empirical literature from longitudinal, experimental, and quasiexperimental studies is reviewed in attempt to identify major determinants of human flourishing, broadly conceived. Measures of human flourishing are proposed. Discussion is given to the implications of a broader conception of human flourishing, and of the research reviewed, for policy, and for future research in the biomedical and social sciences. Discussion will also be given to the methodological implications of attempts to study numerous outcomes at once and to a proposed movement towards outcome-wide longitudinal designs for causal inference. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop TOMORROW (10/17) - Susan Murphy

by Connor Jerzak

*FINAL REMINDER --- Applied Statistics Workshop TOMORROW (10/17) at 12 noon* *Lunch provided --- All are welcome * --------------------------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------------------------- Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) this Wednesday (10/17). The speaker is* Susan Murphy *(Harvard Stats + SEAS) who will be presenting her work "Stratified Micro-Randomized Trials with Applications to Mobile Health". *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 17th at 12 noon - 1:30 pm. *Abstract:* Technological advancements in the field of mobile devices and wearable sensors make it possible to deliver treatments anytime and anywhere to users like you and me. Increasingly the delivery of these treatments is triggered by detections/predictions of vulnerability and receptivity. These observations are likely to have been impacted by prior treatments. Furthermore the treatments are often designed to have an impact on users over a span of time during which subsequent treatments may be provided. Here we discuss our work on the design of a mobile health smoking cessation study in which the above two challenges arose. This work involves the use of multiple online data analysis algorithms. Online algorithms are used in the detection, for example, of physiological stress. Other algorithms are used to forecast at each vulnerable time, the remaining number of vulnerable times in the day. These algorithms are then inputs into a randomization algorithm that ensures that each user is randomized to each treatment an appropriate number of times per day. We develop the stratified micro-randomized trial which involves not only the randomization algorithm but a precise statement of the meaning of the treatment effects and the primary scientific hypotheses along with primary analyses and sample size calculations. Considerations of causal inference and potential causal bias incurred by inappropriate data analyses play a large role throughout. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop Next Week (Wed. 10/17) - Susan Murphy

by Connor Jerzak

Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) next week on Wednesday (10/17). The speaker is* Susan Murphy *(Harvard) who will be presenting her work "Stratified Micro-Randomized Trials with Applications to Mobile Health". *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 17th at 12 noon - 1:30 pm. *Abstract:* Technological advancements in the field of mobile devices and wearable sensors make it possible to deliver treatments anytime and anywhere to users like you and me. Increasingly the delivery of these treatments is triggered by detections/predictions of vulnerability and receptivity. These observations are likely to have been impacted by prior treatments. Furthermore the treatments are often designed to have an impact on users over a span of time during which subsequent treatments may be provided. Here we discuss our work on the design of a mobile health smoking cessation study in which the above two challenges arose. This work involves the use of multiple online data analysis algorithms. Online algorithms are used in the detection, for example, of physiological stress. Other algorithms are used to forecast at each vulnerable time, the remaining number of vulnerable times in the day. These algorithms are then inputs into a randomization algorithm that ensures that each user is randomized to each treatment an appropriate number of times per day. We develop the stratified micro-randomized trial which involves not only the randomization algorithm but a precise statement of the meaning of the treatment effects and the primary scientific hypotheses along with primary analyses and sample size calculations. Considerations of causal inference and potential causal bias incurred by inappropriate data analyses play a large role throughout. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop TOMORROW (Wed. 10/10) - Joscha Legewie

by Connor Jerzak

*FINAL REMINDER --- Applied Statistics Workshop TOMORROW (10/10) at 12 noon* *Lunch provided --- All are welcome * ------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------ Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) tomorrow on Wednesday (10/10). The speaker is* Joscha Legewie* (Harvard Sociology), who will be presenting his work "The Effect of Police Violence on Infant Health. A Pre-Analysis Plan". *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 10th at 12 noon - 1:30 pm. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop Next Week (Wed. 10/10) - Joscha Legewie

by Connor Jerzak

Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) next week on Wednesday (10/10). The speaker is* Joscha Legewie* (Harvard Sociology), who will be presenting his work "The Effect of Police Violence on Infant Health. A Pre-Analysis Plan". *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 10th at 12 noon - 1:30 pm. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

Applied Statistics Workshop TOMORROW (Wed. 10/3) - Naoki Egami

by Connor Jerzak

*FINAL REMINDER --- Applied Statistics Workshop TOMORROW (10/3) at 12 noon* *Lunch provided --- All are welcome * ------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------ Dear workshop community, We will convene for the Applied Statistics Workshop (Gov 3009) next week on Wednesday (10/3). The speaker is* Naoki Egami* (Princeton), who will be presenting his paper "Causal Diffusion Analysis with Stationarity: How Hate Crimes Diffuse across Space" (paper link here <https://scholar.princeton.edu/negami/publications/identification-causal-dif…>). *Where:* CGIS Knafel Building, Room K354 (see this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When: *Wednesday, October 3rd at 12 noon - 1:30 pm. *Abstract:* Although social scientists have long been interested in the process through which ideas and behavior diffuse, the identification of causal diffusion effects, also known as peer effects, remains challenging. Many scholars consider the commonly used assumption of no omitted confounders to be untenable due to contextual confounding and homophily bias. To address this long-standing identification problem, I introduce a class of *stationary* causal directed acyclic graphs (DAGs), which represent the time-invariant nonparametric causal structure. I first show that this stationary causal DAG implies a new statistical test that can detect a wide range of biases, including the two types mentioned above. The proposed test allows researchers to empirically assess the contentious assumption of no omitted confounders. In addition, I develop a difference-in-difference style estimator that can directly correct biases under an additional parametric assumption. Leveraging the proposed methods, I study the spatial diffusion of hate crimes in Germany. After correcting large upward bias in existing studies, I find hate crimes diffuse only to areas that have a high proportion of school dropouts. To highlight the general applicability of the proposed approach, I also analyze the network diffusion of human rights norms. The proposed methodology is implemented in a forthcoming open source software package. *All are welcome! Lunch is provided! * Best, Connor Jerzak Applied Statistics Workshop -- Graduate Student Coordinator An anonymous feedback form for the workshop can be found here at this link <https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-…>. Workshop listserv sign-up at this link <https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.

5 years, 6 months

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gov3009-l October 2018