方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 在线文档收集× | Web Scraping× | |
|---|---|---|
| 领域 | 调查方法论 | 调查方法论 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s (digital / web era) | Late 1990s–2000s |
| 提出者≠ | Adapted from traditional document analysis; digital form emerged with widespread internet adoption | Early internet practitioners; systematised in research contexts from the late 1990s onward |
| 类型≠ | Qualitative / mixed-methods data collection technique | Automated digital data collection technique |
| 开创性文献≠ | Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. DOI ↗ | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 |
| 别名 | digital document collection, web document gathering, online archival data collection, digital records collection | web harvesting, screen scraping, web crawling, automated data extraction |
| 相关 | 5 | 5 |
| 摘要≠ | Online document collection is the systematic process of identifying, retrieving, and compiling digital documents — including web pages, institutional publications, social media posts, policy documents, and digital archives — as primary or supplementary research data. It extends classical document analysis into internet-mediated environments, enabling researchers to access large, geographically dispersed corpora without fieldwork travel or physical archive access. | 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. |
| ScholarGate数据集 ↗ |
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