विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| मोबाइल सर्वेक्षण× | एपीआई-आधारित डेटा संग्रह× | |
|---|---|---|
| क्षेत्र | सर्वेक्षण पद्धति | सर्वेक्षण पद्धति |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | Late 2000s–2010s (accelerated with smartphone adoption, ~2007–2015) | 2000s–2010s (formalized as a research method) |
| प्रवर्तक≠ | Emerged from web survey methodology researchers (Couper, Buskirk, Toepoel, and others) | Emerged from computational social science and web 2.0 platform practices |
| प्रकार≠ | Quantitative / mixed data collection technique | Digital data collection technique |
| मौलिक स्रोत≠ | Toepoel, V., & Lugtig, P. (2014). What happens if you offer a mobile option to your web panel? Evidence from a probability-based panel of internet users. Social Science Computer Review, 32(4), 544–560. DOI ↗ | Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648 |
| उपनाम | smartphone survey, mobile web survey, mobile questionnaire, m-survey | API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection |
| संबंधित≠ | 6 | 5 |
| सारांश≠ | A mobile survey is a self-report questionnaire designed and administered through smartphones or tablets, either via a mobile-optimized web browser or a dedicated app. As mobile devices became the dominant mode of internet access globally, surveys must be built for small screens, touch interaction, and variable connectivity. Mobile surveys are used across social science, public health, market research, and organizational studies when reaching respondents in their natural, everyday context is a priority. | 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 ↗ |
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