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October 15: Elections, Public Opinion and Data Science

RSVP BELOW!

Thank you to NYU for hosting us.

With the election next month we teamed up with NYAAPOR to present three talks about Elections and Public Opinion.

The R in Government Conference happens October 28-30 so we are giving away two tickets after the talks. All members of the group can use code nyhackr for a 20% discount on tickets.

Everybody attending must RSVP at nyhackr.org. There is a charge for in-person and virtual tickets are free. In-person registration closes at 3 PM the day of the talk.

Fake it Till You Make it: Behind the Scenes of Bot-Driven Popularity:My paper examines how fake social media accounts boost politicians’ online popularity and this phenomenon’s subsequent spillover on traditional news coverage. Using the ‘Botometer’ algorithm, I assessed the proportion of bot accounts engaging with tweets from 382 U.S. Congress members on Twitter.

About Manu:I am a computational social scientist and doctoral candidate in Political Science at Columbia University, specializing in Comparative Politics and Statistical Methodology. My research leverages advanced techniques in causal inference, machine learning, and Bayesian statistics to explore political behavior and social media dynamics. My work has earned recognition, including the 2023 Best Student Paper Award in Information, Technology, and Politics and an early career fellowship from the American Political Science Association. Before graduate school, I was a Research Specialist II at Princeton University’s Empirical Studies of Conflict project and a Predictive Analytics Fellow at the United Nations Office for the Coordination of Humanitarian Affairs.

Improving Survey Experiments with Pre-Post Designs:Grow Progress has run well over a thousand survey experiments on behalf of our politics and advocacy clients in the 2024 cycle. This type of pre-testing creative before a broader rollout is increasingly a best practice in campaign work, with most major campaigns, party bodies, and large PACs extensively testing their ads. In this talk, I’ll share some internal research clarifying which experiments tend to benefit most from these designs.

About Andy:Andy is a senior data scientist at Grow Progress, where he works on GP’s platform for fast, cost-effective, and easily interpretable message testing. Some recurring themes of his work are modern methods for survey weighting, efficient estimation of causal effects, and scalable Bayesian inference.

Deciphering News Article Engagement in the Digital Era: Insights into Public Sentiment through Supervised Machine Learning Models:2020 was marked with a series of unprecedented events, such as the pandemic, the murder of George Floyd, and the crucial 2020 U.S. presidential election. In a survey conducted by the Pew Research Center in 2020, a little over half of the respondents (53%) claim that they got their news from social media and digital platforms. Thus, an increasing number of individuals actively participated in discussions on various platforms, including commenting on media platforms. As discussions around these events proliferated across social media and news outlets, understanding the factors driving the popularity of articles became paramount. Articles were collected from The NY Times to understand what features influence popularity. Supervised machine learning models, including linear, ridge, lasso, random forest, and gradient boosting regressions, were employed.

Anusha Natarajan:Anusha Natarajan is currently a graduate student at Columbia University, studying quantitative methods in the social sciences with a data science focus. She is passionate about bringing in the social and data science worlds together to make sense of the data visually and statistically. Anusha has conducted social science research quantitatively and qualitatively inside and outside the university. In her undergraduate years, she took data driven approaches to improve student voter registration and voting rates in implementing reforms to improve STEM voter rates in the 2020 election. She worked as an intern at the Pew Research Center, researching voter trends across.

Doors open at 6:30 PM America/New_York with pizza. The talk, and livestream, begins at 7:00 PM America/New_York.

Remember, register below!

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