Porovnat metody

	Vzdálené web scraping	Sbírání dat pomocí API
Obor	Metodologie dotazníkových šetření	Metodologie dotazníkových šetření
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	2000s–2010s (cloud infrastructure era)	2000s–2010s (formalized as a research method)
Tvůrce	Distributed computing and web automation communities	Emerged from computational social science and web 2.0 platform practices
Typ	Automated remote data collection technique	Digital data collection technique
Původní zdroj	Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571	Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648
Další názvy	cloud web scraping, server-side scraping, remote automated data extraction, distributed web scraping	API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection
Příbuzné	3	5
Shrnutí	Remote web scraping is a data collection approach in which automated scripts or bots harvest publicly accessible web content — text, tables, metadata, or links — running on remote servers or cloud infrastructure rather than on the researcher's local machine. This separation allows continuous, large-scale, or geographically distributed crawling that local setups cannot sustain, making it particularly suited to longitudinal or high-volume data collection tasks.	API-based data collection is a systematic technique in which a researcher sends structured requests to an application programming interface to retrieve data automatically from digital platforms, databases, or services. It is the primary method used in computational social science to gather large-scale social media records, government open data, financial data streams, and scientific repository content in machine-readable formats such as JSON or XML, enabling reproducible and scalable data acquisition that manual collection cannot match.