方法对比

	Web Scraping	内容分析
领域	调查方法论	质性
方法族	Process / pipeline	Process / pipeline
起源年份	Late 1990s–2000s	Systematised through Krippendorff's methodology work; 4th edition 2018
提出者	Early internet practitioners; systematised in research contexts from the late 1990s onward	Klaus Krippendorff (systematic formulation); roots in early 20th-century communications research
类型	Automated digital data collection technique	Qualitative / mixed-method research technique
开创性文献	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
别名	web harvesting, screen scraping, web crawling, automated data extraction	İçerik Analizi, systematic content coding, quantitative content analysis
相关	5	5
摘要	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.