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Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Automatizované získavanie webových dát pomocou web scrapingu× | Zber dát prostredníctvom API× | |
|---|---|---|
| Odbor | Metodológia dotazníkových prieskumov | Metodológia dotazníkových prieskumov |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | Late 1990s–2000s | 2000s–2010s (formalized as a research method) |
| Tvorca≠ | Early internet practitioners; systematised in research contexts from the late 1990s onward | Emerged from computational social science and web 2.0 platform practices |
| Typ≠ | Automated digital data collection technique | Digital data collection technique |
| Pôvodný 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 |
| Ďalšie názvy | web harvesting, screen scraping, web crawling, automated data extraction | API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection |
| Príbuzné | 5 | 5 |
| Zhrnutie≠ | 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. | 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. |
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