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| 웹 스크래핑× | 문헌 수집× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | Late 1990s–2000s | 19th–20th century historical methods; contemporary social-science codification c. 2000s |
| 창시자≠ | Early internet practitioners; systematised in research contexts from the late 1990s onward | Rooted in historical and social science traditions; systematized by Lindsay Prior and Glenn Bowen |
| 유형≠ | Automated digital data collection technique | Qualitative / mixed data-collection technique |
| 원전≠ | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 | Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. DOI ↗ |
| 별칭 | web harvesting, screen scraping, web crawling, automated data extraction | document analysis, documentary method, document review, secondary document analysis |
| 관련≠ | 5 | 3 |
| 요약≠ | 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. | Document collection is a systematic data-collection technique in which the researcher gathers and reviews existing written, visual, or digital records — such as reports, meeting minutes, policies, letters, photographs, or institutional records — as primary or supplementary evidence. It is widely used in qualitative, historical, and mixed-methods research and can stand alone or complement interviews and observation. |
| ScholarGate데이터셋 ↗ |
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