Multi-source API-based Data Collection
Multi-source API-based data collection is a systematic technique in which a researcher simultaneously or sequentially queries two or more application programming interfaces (APIs) to harvest digital data for a research project. By drawing from multiple platforms or services — such as social media APIs, government open-data portals, or scientific data repositories — researchers can build richer, more representative datasets than any single source permits. The method is especially prominent in computational social science, digital humanities, public health surveillance, and environmental monitoring.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063–1064. · DOI 10.1126/science.346.6213.1063
- Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. · ISBN 978-0691158648
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.