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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Ukusanyaji wa Data wa Kihisi kwa Njia ya Simu×Ukusanyaji Data kwa kutumia API×
NyanjaMetodolojia ya DodosoMetodolojia ya Dodoso
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili2000s–2010s (aligned with smartphone proliferation)2000s–2010s (formalized as a research method)
MwanzilishiEmerging from ubiquitous computing and digital health research communities; no single originatorEmerged from computational social science and web 2.0 platform practices
AinaPassive and active data collection via telephone/smartphone sensorsDigital data collection technique
Chanzo asiliaLane, 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
Majina mbadalaphone-based sensor data collection, telephone-mediated sensor monitoring, mobile phone sensor data collection, TASDCAPI data harvesting, API-driven data collection, programmatic data retrieval, API research data collection
Zinazohusiana55
MuhtasariTelephone-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.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

Nenda kwenye utafutaji Pakua slaidi

ScholarGateLinganisha mbinu: Telephone-assisted Sensor Data Collection · API-based Data Collection. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare