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| Telefonassisteret indsamling af sensordata× | API-baseret dataindsamling× | |
|---|---|---|
| Fagområde | Surveymetodologi | Surveymetodologi |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 2000s–2010s (aligned with smartphone proliferation) | 2000s–2010s (formalized as a research method) |
| Ophavsperson≠ | Emerging from ubiquitous computing and digital health research communities; no single originator | Emerged from computational social science and web 2.0 platform practices |
| Type≠ | Passive and active data collection via telephone/smartphone sensors | Digital data collection technique |
| Oprindelig kilde≠ | Lane, N. D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. T. (2010). A survey of mobile phone sensing. IEEE Communications Magazine, 48(9), 140–150. DOI ↗ | Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648 |
| Aliasser | phone-based sensor data collection, telephone-mediated sensor monitoring, mobile phone sensor data collection, TASDC | API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection |
| Relaterede | 5 | 5 |
| Resumé≠ | Telephone-assisted sensor data collection uses participants' mobile phones as sensing platforms to gather continuous or triggered streams of physical and behavioral data — such as movement, location, and ambient sound — without requiring them to attend a lab. A research application installed on the phone captures sensor readings and transmits them to a central server, enabling large-scale, ecologically valid measurement of real-world behavior over days or weeks. | 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. |
| ScholarGateDatasæt ↗ |
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