방법 비교

	API 기반 파일럿 테스트 데이터 수집	웹 스크래핑
분야	조사방법론	조사방법론
계열	Process / pipeline	Process / pipeline
기원 연도	2000s–2010s	Late 1990s–2000s
창시자	Convergence of survey pilot-testing tradition (Presser et al., 2004) and computational social science API methods (Salganik, 2018)	Early internet practitioners; systematised in research contexts from the late 1990s onward
유형	Applied data-collection variant	Automated digital data collection technique
원전	Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 978-0691158648	Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571
별칭	pilot API data collection, pre-tested API harvesting, API data collection pilot study, pilot-validated API scraping	web harvesting, screen scraping, web crawling, automated data extraction
관련	4	5
요약	Pilot-tested API-based data collection is a structured digital data-gathering approach in which a researcher designs an API query or harvesting script and then runs a small-scale trial before executing the full collection. The pilot phase exposes authentication issues, rate-limit constraints, schema inconsistencies, and coverage gaps, enabling targeted refinements that protect the integrity and completeness of the final dataset. It bridges the software-engineering practice of integration testing with the social-science tradition of instrument pre-testing.	Web scraping is a computational data collection technique in which software automatically retrieves and extracts structured or semi-structured content from websites. Widely used in social science, computational linguistics, economics, and information science, it enables researchers to assemble large datasets from publicly accessible web sources — such as news archives, social media platforms, government portals, and online marketplaces — that would be impractical to collect manually.