So sánh phương pháp

	Thu thập dữ liệu khảo sát qua thiết bị di động	Thu thập dữ liệu dựa trên API
Lĩnh vực	Phương pháp luận khảo sát	Phương pháp luận khảo sát
Họ	Process / pipeline	Process / pipeline
Năm ra đời	Late 2000s–2010s (accelerated with smartphone adoption, ~2007–2015)	2000s–2010s (formalized as a research method)
Người khởi xướng	Emerged from web survey methodology researchers (Couper, Buskirk, Toepoel, and others)	Emerged from computational social science and web 2.0 platform practices
Loại	Quantitative / mixed data collection technique	Digital data collection technique
Công trình gốc	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.	Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648
Tên gọi khác	smartphone survey, mobile web survey, mobile questionnaire, m-survey	API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection
Liên quan	6	5
Tóm tắt	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.