Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Пилотно тестване на събиране на данни чрез API× | Уеб скрапинг× | |
|---|---|---|
| Област | Методология на проучванията | Методология на проучванията |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2000s–2010s | Late 1990s–2000s |
| Създател≠ | 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 |
| Тип≠ | Applied data-collection variant | Automated digital data collection technique |
| Основополагащ източник≠ | 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 |
| Други названия | 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 |
| Свързани≠ | 4 | 5 |
| Резюме≠ | 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. |
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