Methoden vergleichen

	Longitudinal Web Scraping	Web Scraping
Fachgebiet	Umfragemethodik	Umfragemethodik
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	2000s–2010s	Late 1990s–2000s
Urheber	Emergent practice in computational social science; formalized across internet research community	Early internet practitioners; systematised in research contexts from the late 1990s onward
Typ	Automated longitudinal data collection	Automated digital data collection technique
Wegweisende Quelle	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
Aliasnamen	repeated web scraping, time-series web data collection, longitudinal crawling, panel web scraping	web harvesting, screen scraping, web crawling, automated data extraction
Verwandt	5	5
Zusammenfassung	Longitudinal web scraping is a data collection technique that uses automated scripts to extract content from websites at multiple, predefined time points. By revisiting the same web sources repeatedly, researchers build a time-series dataset that captures how online content, prices, discourse, or behavior evolves. It is widely used in computational social science, economics, political science, health research, and digital humanities to study change without relying on retrospective self-report.	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.