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

Social media has changed the way politics is practiced and the way it is studied by social scientists and journalists, introducing a number of technical obstacles as well as scientific opportunities. At CSMaP, we support lab-based, interdisciplinary research that examines a broad range of questions at the intersection of social media and politics.

New York University | New York City, NY

RECENT NEWS

CSMaP Seminar Series

This fall — ahead of the 2020 elections — we’ll bring together leading scholars to explore the relationship between new media technologies and democratic politics. Our CSMaP Seminar Series aims to highlight the latest research and identify future research we need in the lead-up to and aftermath of the elections. Speakers will present research on topics such as fighting the effects of misinformation, social media and protest participation, electoral interference strategies, and how political elites are responding to new information environments. Click through for more details and registration information.

Social Media and Democracy: New Book Out September 2020

Our co-director, Joshua Tucker, has co-edited a volume exploring the field of social media research with Nathaniel Persily, co-director of the Stanford Cyber Policy Center. The text chronicles the recent explosion of research at the intersection of social media and democracy — and the resulting new field that brings together political scientists, economists, psychologists, communication scholars, and other researchers from different corners of academia. The book, out September 2020, will be published by Cambridge University Press. Click through to read the final chapter, which details the legal barriers preventing access to key social media datasets, and the ethical quandaries surrounding analyses of such data.

National Science Foundation awards CSMaP researchers a $199,596 COVID-19 RAPID Grant

In recent months, the global COVID-19 pandemic has been accompanied by an infodemic, exposing shortcomings not only in the diffusion of high quality information through online networks, but also in our understanding of who is most susceptible to believing false and misleading information during times of crisis. With the support of the NSF RAPID Grant, we seek to study to study susceptibility to false and misleading news around COVID-19, as well as to test how the new pandemic environment impacts assessment of the veracity of news – both COVID-related and political – over the course of the 2020 election campaign.

FEATURED WORK

APSR identifies SMaPP research as one of 2019's most influential articles

Journal Article

Are legislators responsive to the priorities of the public? We answer this question with fine-grained temporal analyses of Twitter messages by legislators and the public during the 113th US Congress. We find that legislators are more likely to follow, than to lead, discussion of public issues, results that hold even after controlling for the agenda-setting effects of the media. APSR ranked this article as one of the most influential articles of 2019.

New SMaPP research published in Public Opinion Quarterly

Journal Article

“Clickbait” headlines designed to entice people to click are frequently used by both legitimate and less-than-legitimate news sources. Contemporary clickbait headlines tend to use emotional partisan appeals, raising concerns about their impact on consumers of online news. This article reports the results of a pair of experiments with different sets of subject pools: one conducted using Facebook ads that explicitly target people with a high preference for clickbait, the other using a sample recruited from Amazon’s Mechanical Turk.

Working paper on measuring the prevalence of online hate speech

Working Paper

We offer a new approach to measuring the real-time prevalence of online hate, using both context specific data and data produced by a large random sample of users; employing multiple methods of text classification; and measuring not only the volume, but also the proportion, and number of unique users producing it.

VIEW ALL ACADEMIC ARTICLES

VIEW ALL DATA REPORTS

VIEW ALL OP-EDS

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