Making Research Easier: Introducing Collections and Snapshots in Meta Content Library API
UPDATED NOV 10, 2025
Usability and Collaboration at the Core
MCL API is a vital tool for researchers analyzing public Facebook and Instagram data. As research projects grow in complexity and often involve multiple team members, the need for robust organization and collaboration tools becomes critical. The new Collections and Snapshot Mode features directly address these needs, helping to make the tool more usable and collaborative for both individual researchers and their teams.
Collections: Organize, Collaborate and Manage Projects Together
What’s New:
Collections introduce a flexible, project-based structure for managing queries and results. Instead of handling individual queries in isolation, researchers can now group related queries and results under a single project. This makes it easier to:
- Collaborate in Real Time: Share entire workspaces with colleagues, ensuring everyone has access to the same queries, results, and project structure.
- Organize Complex Projects: Manage multi-step research projects in a single, navigable space.
- Manage Permissions: Manage Permissions: you can choose at any time to change your collections and queries’ visibility to public or private, giving you control over who can view your queries.
Example Use Cases:
- Team Collaboration: A group studying social sentiment can share a collection containing all relevant queries and results, ensuring everyone is aligned and can contribute to the analysis.
- Longitudinal Study: A researcher tracking online discourse around elections can create a workspace for “UK Elections 2024,” add queries for candidates, parties, and comments, and organize results by time period.
For step-by-step instructions, see the Collections Guide.
Snapshot Mode: Reliable Reproducibility and Transparent Collaboration
What’s New:
Snapshot Mode allows researchers to preserve certain statistical results from async queries for up to one year, even as the underlying data changes or is deleted. This is a breakthrough for reproducibility and collaborative verification in social media research and will enable the following:
- Reproducibility for teams: Teams can share immutable snapshots, ensuring that others can analyze and review certain results from the same dataset, even months later.
- Forward looking historical analysis: By preserving statistical data from dynamic datasets over time, snapshots allow researchers to track and compare trends even as the underlying content evolves.
- Transparent review: Snapshots can be shared with reviewers or collaborators who also have access to MCL API in the same cleanroom environment, supporting verification and transparent research practices.
- Privacy preserving practices: Snapshots automatically update every 30 days to reflect the current state of the content (e.g., remove deleted or non-public content, etc.) helping to respect user preferences and build trust with collaborators.
Example Use Cases:
- Replicating Results: A researcher is analyzing engagement on public posts and wants to share their findings with a colleague for the purpose of later research or publication. By sharing a snapshot, collaborators with access to MCL API can replicate results from the same underlying dataset to understand and verify the researcher’s findings.
- Policy Impact Analysis: A researcher tracks changes in public sentiment before and after a major policy announcement. Snapshots allow them to compare datasets across time, even if there were changes to the underlying data (e.g., a user deleted their content).
For more details, see the Snapshot Mode Documentation.