New Analytics API for researchers learning Fb Web page information
Today we’re launching the Facebook Open Research & Transparency (FORT) Analytics API for researchers. This release includes a collection of API endpoints that scientists can use to identify trends on Facebook Pages and how they have evolved over time. You can use this insight to focus on specific pages that are of interest.
We designed this API specifically for the academic community to perform longitudinal analysis on time series data. With the launch of the FORT Pages API in 2020, and now the Analytics API, we will continue to develop a product roadmap that will focus on sharing new types of Facebook and Instagram data with the academic research community, as well as additional analytics endpoints concentrated.
Analytics API functions
With the FORT Analytics API, we are offering three new endpoints. Each of these data is aggregated time series data collected at daily intervals and includes:
- Lifetime followers (number of users who have ever followed a page) by country per page.
- Page administrator number of posts (only applies to posts by page administrators and not to user posts)
- Number of page engagements, where engagement is defined as the total number of likes, comments, clicks, and approvals for posts created on this page
Unlike other research-related APIs, these endpoints make it easier to query on any public Facebook page. (You can find more information on Facebook datasets that we make available to researchers here.)
For technical documentation click here.
Current Analytics: These endpoints provide aggregated metrics on Facebook Pages. They are designed to help researchers observe and analyze page inclusion patterns and use that analysis to decide which pages to focus on. This saves time and effort. Our systems take a snapshot of page activity once a day and make this information available to you via the Pages API. As a result, these aggregations are directional (as opposed to data that is dynamically generated for each query).
Historical Page Data: Using these endpoints, there may be small historical inaccuracies in the counts. For example, the Center for Disease Control page appears to have lost a few hundred followers in January, most likely due to deletion of user accounts, etc. We currently consider this to be an acceptable inaccuracy in order to continue delivering high quality research, but we will continue to monitor it and include it in future updates. Note that a user who deletes a post, dislikes a post, or deletes a comment will not be included in the analysis. In other words, the data does not take into account deletions of any content.
How to access the FORT Analytics API
If you are a Social Science One Fellow, you will have standard access to this API through the FORT platform. If you are not an SS1 researcher but are interested in using this API, apply here to join the Social Science One community.
While we don’t apply a formal query size limit, for best performance we recommend the following:
- No more than 250 page IDs in a single API call
- Request no more than 10,000 records in a single API call
Please refer to this documentation for more information.
Via the Facebook Open Research and Transparency Platform
The Facebook Open Research and Transparency (FORT) platform makes responsible research easier by enabling flexible access to valuable data. The platform has validated data protection and security measures such as data access controls and has been tested for penetration by internal and external experts.
The FORT platform runs on an opinion-based version of JupyterHub, an open source tool that is widely used by the academic community. The FORT platform supports several standard programs, including SQL, Python and R, as well as a special bridge to certain Facebook Graph APIs.
Researchers can publish research done with this data without Facebook’s permission. As with other research conducted under the Research Data Agreement, Facebook has the right to review (not approve or reject) research results prior to publication and to remove any confidential or personally identifiable information.