Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сбор данных через мобильные API× | Веб-скрейпинг× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2007–2010 (mainstream smartphone era) | Late 1990s–2000s |
| Автор метода≠ | Emerged from mobile computing and REST/web API proliferation (Fielding, 2000; widespread adoption ~2007–2010 with smartphone ecosystem) | Early internet practitioners; systematised in research contexts from the late 1990s onward |
| Тип≠ | Digital data collection technique | Automated digital data collection technique |
| Основополагающий источник≠ | Luce, M. F., Kahn, B. E., & Malhotra, N. K. (2016). Capturing consumer experiences with mobile research methods. Journal of Consumer Research, 42(6), 949–965. link ↗ | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 |
| Другие названия | mobile API data collection, smartphone API data harvesting, mobile app API research data collection, API-driven mobile data collection | web harvesting, screen scraping, web crawling, automated data extraction |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Mobile API-based data collection uses mobile devices (smartphones, tablets) to query application programming interfaces — structured web endpoints that return machine-readable data — enabling researchers to gather behavioral, contextual, sensor-enriched, or platform-generated data in real time from participants in their natural environments. It combines the ubiquity of mobile hardware with the scalability and standardization of RESTful or GraphQL APIs. | 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. |
| ScholarGateНабор данных ↗ |
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