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| 웹 스크래핑× | 콘텐츠 분석× | |
|---|---|---|
| 분야≠ | 조사방법론 | 질적 방법 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | Late 1990s–2000s | Systematised through Krippendorff's methodology work; 4th edition 2018 |
| 창시자≠ | Early internet practitioners; systematised in research contexts from the late 1990s onward | Klaus Krippendorff (systematic formulation); roots in early 20th-century communications research |
| 유형≠ | Automated digital data collection technique | Qualitative / mixed-method research technique |
| 원전≠ | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 | Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage. ISBN: 978-1506395661 |
| 별칭≠ | web harvesting, screen scraping, web crawling, automated data extraction | İçerik Analizi, systematic content coding, quantitative content analysis |
| 관련 | 5 | 5 |
| 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. | Content analysis is a systematic research technique for reducing text, visual, or media material into coded categories so that patterns can be counted, compared, and interpreted. Formalised by Klaus Krippendorff in his widely cited methodology textbook (latest edition 2018), the method sits at the boundary of qualitative and quantitative inquiry: it imposes structured, replicable coding on inherently meaning-laden material. |
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