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API数据收集×Mobile Experience Sampling×
领域调查方法论调查方法论
方法族Process / pipelineProcess / pipeline
起源年份2000s–2010s (formalized as a research method)1983
提出者Emerged from computational social science and web 2.0 platform practicesMihaly Csikszentmihalyi & Reed Larson
类型Digital data collection techniqueIntensive longitudinal data collection technique
开创性文献Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗
别名API data harvesting, API-driven data collection, programmatic data retrieval, API research data collectionESM, Experience Sampling Method, Ecological Momentary Assessment, EMA
相关55
摘要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.
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ScholarGate方法对比: API-based Data Collection · Mobile Experience Sampling. 于 2026-06-15 检索自 https://scholargate.app/zh/compare