Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Збір даних на основі мобільних API× | Збір даних на основі API× | |
|---|---|---|
| Галузь | Методологія опитувань | Методологія опитувань |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2007–2010 (mainstream smartphone era) | 2000s–2010s (formalized as a research method) |
| Автор методу≠ | Emerged from mobile computing and REST/web API proliferation (Fielding, 2000; widespread adoption ~2007–2010 with smartphone ecosystem) | Emerged from computational social science and web 2.0 platform practices |
| Тип | Digital data collection technique | Digital data collection technique |
| Основоположне джерело≠ | 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 ↗ | Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648 |
| Інші назви | mobile API data collection, smartphone API data harvesting, mobile app API research data collection, API-driven mobile data collection | API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | 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. | API-based data collection is a systematic technique in which a researcher sends structured requests to an application programming interface to retrieve data automatically from digital platforms, databases, or services. It is the primary method used in computational social science to gather large-scale social media records, government open data, financial data streams, and scientific repository content in machine-readable formats such as JSON or XML, enabling reproducible and scalable data acquisition that manual collection cannot match. |
| ScholarGateНабір даних ↗ |
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