विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| मोबाइल सेंसर डेटा संग्रह× | एपीआई-आधारित डेटा संग्रह× | |
|---|---|---|
| क्षेत्र | सर्वेक्षण पद्धति | सर्वेक्षण पद्धति |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | Mid-2000s (smartphone-era formalization ~2006–2010) | 2000s–2010s (formalized as a research method) |
| प्रवर्तक≠ | Andrew Campbell, Tanzeem Choudhury, and colleagues (early smartphone sensing research); broader field of ubiquitous computing | Emerged from computational social science and web 2.0 platform practices |
| प्रकार≠ | Passive and active quantitative data collection technique | Digital data collection technique |
| मौलिक स्रोत≠ | 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 |
| उपनाम | mobile sensing, smartphone sensor data collection, wearable sensor data collection, passive mobile data collection | API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection |
| संबंधित≠ | 4 | 5 |
| सारांश≠ | Mobile sensor data collection uses the built-in sensors of smartphones, tablets, or wearable devices to capture behavioral, physiological, and environmental data in real-world settings. Sensors such as accelerometers, GPS, heart rate monitors, ambient light detectors, and microphones record data passively or on demand, enabling researchers to study human behavior with high temporal resolution outside the laboratory. | 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. |
| ScholarGateडेटासेट ↗ |
|
|