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New Analytics API for researchers studying Facebook Page data

Today we are launching the Facebook Open Research & Transparency (FORT) Analytics API for researchers. This release includes a collection of API endpoints that helps academics identify trends on Facebook Pages and how they’ve evolved over time. You can leverage these insights to focus on specific Pages that are of interest.

We designed this API specifically for the academic community to conduct longitudinal analyses with time series data. With the launch of FORT Pages API in 2020 and now the Analytics API, we will continue to develop a product roadmap focused on sharing new types of Facebook and Instagram data with the academic research community, as well as additional analytics endpoints.

Analytics API features

With the FORT Analytics API, we are offering three new endpoints. Each of these are aggregated, time-series data, captured at daily intervals and include:

  1. Lifetime follower count (number of users who have ever followed a Page) by country per Page.
  2. Page admin Post count (applies only to Posts made by Page admins and not to user posts)
  3. Page engagement count, where engagement is defined as total number of likes, comments, clicks and shares on Posts created on that Page

Unlike other research-related APIs, these endpoints facilitate queries across the entirety of public Facebook Pages. (You can learn more about Facebook data sets that we make available to researchers here.)

For technical documentation, click here.

Important considerations

Current Analytics data: These endpoints provide aggregate metrics on Facebook Pages. They are designed to help researchers observe and analyze engagement patterns of Pages and leverage that analysis to decide which Pages to focus on, saving time and effort. Our systems take a snapshot of Page activity once per day and provide that information to you via the Pages API. Consequently, these aggregations are directionally accurate (as opposed to data which is dynamically generated for each query).

Historical Page data: When using these endpoints you may encounter small, historical inaccuracies with the counts. For instance, the Center for Disease Control Page seems to have lost a few hundred followers in January, most likely due to user account deletions etc. For now, we consider this an acceptable amount of inaccuracy to still deliver high quality research, but we continue to monitor these to incorporate into future updates. Note that a user deleting a Post, unliking a Post, or deleting a Comment will not be reflected in the analytics. In other words, the data does not account for content deletions.

How to access the FORT Analytics API

If you are a grantee of Social Science One, you will have default access to this API through the FORT platform. If you are not an SS1 researcher but are interested in using this API, please apply to join the Social Science One community here.

Technical limitations
While we won’t apply any formal limit on query size, we recommend the following for best performance:

  • No more than 250 page ids in a single API call
  • Request no more than 10,000 records in a single API call

See this documentation for more details.

About the Facebook Open Research and Transparency Platform

The Facebook Open Research and Transparency (FORT) Platform facilitates responsible research by providing flexible access to valuable data. The platform is built with validated privacy and security protections, such as data access controls, and has been penetration-tested by internal and external experts.

The FORT platform runs on an opinionated version of JupyterHub, an open source tool that is widely used by the academic community. The FORT platform supports multiple standard programs, including SQL, Python, and R, and a specialized bridge to specific Facebook Graph APIs.

Publication guidelines

Researchers may publish research conducted using this data without Facebook’s permission. As with other research conducted under the Research Data Agreement, Facebook is entitled to review (not approve or reject) research prior to publication, and remove any confidential or personally identifiable information.

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