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| API 기반 데이터 수집× | 모바일 경험 표본 추출× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2000s–2010s (formalized as a research method) | 1983 |
| 창시자≠ | Emerged from computational social science and web 2.0 platform practices | Mihaly Csikszentmihalyi & Reed Larson |
| 유형≠ | Digital data collection technique | Intensive longitudinal data collection technique |
| 원전≠ | Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648 | Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗ |
| 별칭 | API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection | ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA |
| 관련 | 5 | 5 |
| 요약≠ | 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. | Mobile Experience Sampling (ESM) is an intensive longitudinal data-collection technique in which participants respond to brief, repeated questionnaires delivered to their smartphones at random or scheduled intervals throughout the day. By capturing thoughts, feelings, behaviors, and context at or near the moment they occur, ESM minimises retrospective recall bias and provides a high-resolution picture of psychological and behavioral fluctuations in everyday life. |
| ScholarGate데이터셋 ↗ |
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