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| Fjern-web-scraping× | Web Scraping× | |
|---|---|---|
| Fagområde | Surveymetodologi | Surveymetodologi |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 2000s–2010s (cloud infrastructure era) | Late 1990s–2000s |
| Ophavsperson≠ | Distributed computing and web automation communities | Early internet practitioners; systematised in research contexts from the late 1990s onward |
| Type≠ | Automated remote data collection technique | Automated digital data collection technique |
| Oprindelig kilde | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 |
| Aliasser | cloud web scraping, server-side scraping, remote automated data extraction, distributed web scraping | web harvesting, screen scraping, web crawling, automated data extraction |
| Relaterede≠ | 3 | 5 |
| Resumé≠ | 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. | 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. |
| ScholarGateDatasæt ↗ |
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