The Center for Social Media and Politics – We are committed to the scientific research of how social media impacts politics.

NYU’s Center for Social Media and Politics is an academic research institute dedicated to studying how social media impacts politics, policy, and democracy.

FEATURED WORK

New Book: Social Media and Democracy

Research on social media and democracy has exploded in recent years, launching a new field bringing together political scientists, economists, psychologists, and others. This new book, co-edited by our Co-Director Joshua Tucker, explores the state of the field and prospects for reform.

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Do Twitter Warning Labels Work?

Jack Dorsey and Mark Zuckerberg during their Senate hearing

In Fall 2020, Twitter started putting warning labels on hundreds of thousands of tweets. But, according to our analysis, tweets with warning labels continued to spread — and Trump’s tweets with warning labels actually spread further than those without.

Who Shares Fake News on Facebook?

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A small percentage of Americans, less than 9 percent, shared links to so-called “fake news” sites on Facebook during the 2016 presidential election campaign, but this behavior was disproportionately common among people over the age of 65. Read our study in the journal Science Advances.

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A COMMITMENT TO OPEN SCIENCE

As part of our project to construct comprehensive data sets and to empirically test hypotheses related to social media and politics, we have developed a suite of open-source tools and modeling processes.

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Downloads of our open source software

You can explore and download our data collection and analysis tools here.

OPEN SOURCE TOOLS

smappdragon

smappdragon is a low level data parser designed for parsing twitter data.

pysmap

pysmapp is a high-level JSON-parser that extends smapdragon for non-coders

urlExpander

urlExpander is a Python module to quickly and thoroughly expand shortened urls

youtube-data-api

youtube-data-api is a Python client to download public YouTube data about channels, videos, and searches

streamR package

streamR is a package written by Pablo Barbera and published on CRAN that provides access to Twitter’s Streaming API via the R language. The package allows for easy creation of filter, sample and user streams: this involves tooling for creation of an OAuth token, opening a filter connection with twitter that returns real time public statuses based on given terms or parameters, for a given user or users, or a random sample of these statuses (up to 1% of all tweets at any given time, which is the Twitter limit) and functions for reading and parsing the results into a data frame.

Rfacebook package

The Rfacebook package was written by Pablo Barbera, Michael Piccirilli, Andrew Geisler, and Wouter van Attendeldt and published on CRAN. It allows for easy interaction with the Facebook via R and provides many different functions for interacting with the API to obtain information about users, posts and to collect public status updates the mention specific keywords. Some examples of the tooling provided include: functions to create an OAuth token, get posts, likes, reactions, shares, users, getting page insights for a specific time period, getting an adjacency matrix representing a users mutual friend network, general facebook search, facebook group search. The package is built out and includes unit testing.

instaR

instaR package provides a series of functions that allow R users to access Instagram’s API to search for media that mention specific hashtags or were sent from a certain location, to download recent pictures from a given users, and to capture lists of followers.

Local News Dataset

A directory of local news outlets by state and medium. Includes social media accounts for local news outlets.

mediascores

R-package to estimate media scores from url sharing data

WHO WE ARE

Drawing from politics, data science, biology, and psychology, CSMaP is a diverse community of scholars studying the intersection of social media and politics.

Meet our full team

RICHARD BONNEAU

Faculty Director

ZHANNA TERECHSHENKO

Postdoctoral Fellow

JENNIFER LARSON

Research Associate

EDWIN KAMAU

Research/Data Engineer