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Longitudinal Web Scraping

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.

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Longitudinal Web Scraping for Research

Taksonoomiline meetodikirje · process-pipeline / survey-methodology

Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. · ISBN 978-0691158648
Luscombe, A., Dick, K., & Walby, K. (2022). Algorithmic thinking in the public interest: navigating technical, legal, and ethical challenges in government web scraping. Quality & Quantity, 56(3), 1781–1802. · DOI 10.1007/s11135-021-01164-0

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Taxonomic bucketAPI-based Data Collectionmachine-suggested · Relational suggestion, not evidence.Same method familyContent Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketLongitudinal Surveymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSensor Data Collectionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketWeb Scrapingmachine-suggested · Relational suggestion, not evidence.