Resources for researchers

Tools and guides to support your work

Learn the fundamentals of using Twitter data for academic research with our get-started guides or take your current use of our APIs further with tutorials, articles, code samples, and third-party tools.

Guides for getting started

These guides give you the foundational knowledge and skills required to use the Twitter API for research projects. Start here if you are new to Twitter data or using APIs.

This guide looks at the new payload structure, individual fields, and their relevance for academic research

This guide walks through the new operators available to filter and collect Twitter data and discusses design considerations for getting the right data for your research

Don't yet have access to the Twitter API? Check out our step-by-step Getting Started guide for Twitter Developers.

Tutorials, Articles, and Code Samples

These resources can help with intermediate to advanced uses of the Twitter API. Start here if you're familiar with Twitter data and you want to dig deeper into a topic or specific task.

Getting COVID-19 data using filtered stream endpoint

This article is an introduction to Twitter data processing and storage on Amazon Web Services (AWS). It includes details around popular services on AWS, example reference architectures, and code samples.

Python and R are both very popular for common data science tasks. This blog post shows you how to use them together with the Twitter API.

A beginners guide to getting started with the Twitter API in R.

Fiona Pigott (@notFromShrek) demonstrates the art and science of getting a high-quality Tweet sample and doing basic NLP using our standard search API.

Josh Montague (@jrmontag) shows how to collect data around a cultural topic, and apply clustering models to learn more about the people participating in that conversation.

Taylor Swift helps give us an overview of methods for working with Twitter data as a time series to detect trends, from basic operations and transformations to threshold-based methods.


Connect with others using Twitter data for research on our Academic Research forum.

Third-party resources

These are some popular code libraries, analysis tools, and other resources used by researchers and sourced from our conversations with the academic research community.

Note: Inclusion of third-party services on this list is not an endorsement by Twitter, and does not indicate their current compliance status.

  • Libraries and data access
  • Data analysis tools
  • Data visualization tools
  • Infrastructure, databases and hosting

Libraries and data access

These code libraries will help you connect to the Twitter API or access Twitter data:

An easy-to-use Python library for accessing the Twitter API

A python package from Twitter with support for Premium APIs.

A R client for accessing Twitter’s REST and stream APIs

An unofficial Java library for the Twitter API

A Javascript library for Twitter APIs.

A PHP auth wrapper for Twitter API.

A graphical user interface for querying an API and exploring the results returned

A graphical user interface for querying an API and exploring the results returned

A desktop application for hydrating Twitter ID datasets.

A command line tool and Python library for archiving Twitter JSON data.


See Twitter’s full list of community libraries (non-research specific) here.

Data analysis tools

These tools help you set up your analysis of Twitter data.

An interactive development environment for Python

Pandas 

An open source data analysis tool for Python

A collection of packages for data science tasks in R

A tool to explore the new Tweet payload

Add-ons for Microsoft Excel that support social network and content analysis

Open Data Analytics software

The Digital Methods Initiative Twitter Capture and Analysis Toolset (DMI-TCAT) is a set of tools to retrieve and collect tweets from Twitter and to analyze them in various ways

Mecodify is an open-source tool created as part of the Media Conflict and Democratization Project (http://mecodem.eu) to help gather, analyse and visualise Twitter data for use by social science scholars

A free Windows program for keyword, issue, time series, sentiment, gender and content analyses of (mainly) social media texts

Qualitative data analysis software

A community-supported text and social networks analyzer for social media researchers and educators to study public discourse on social media sites

A low level data parser designed for parsing Twitter data

A high level toolkit for dealing with Twitter data

Software to create data science using an intuitive environment

Data visualization tools

These tools help you set up visualizations of Twitter data.

The leading visualization and exploration software for all kinds of graphs and networks

A data visualization package for R

A free Web service for scientists interested in using Twitter content in their research

A Python library for creating statistical graphics

A Social Network Analysis tool

An interactive visualization library in Python

An open source software platform for visualizing complex networks and integrating these with any type of attribute data

Organize complex data into relationship maps

An advanced text analytics visualization tool

A Python library for creating static, animated, and interactive visualization

Mecodify is an open-source tool created as part of the Media Conflict and Democratization Project (http://mecodem.eu) to help gather, analyze and visualize Twitter data for use by social science scholars

Tweet sentiment visualisation app

Infrastructure, databases and hosting solutions

These are some of the most commonly used solutions to store and process Twitter data

Amazon’s cloud platform that provides compute, storage and application services

Google’s cloud platform that provides infrastructure and services

Provides databases and compute services in the cloud

Provides analytics and data services

A general purpose. Document-based database solution

A native graph database platform

Learn more about Twitter data for academic researchers