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方法族Process / pipelineProcess / pipeline
起源年份1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s1950s (Berelson 1952; Krippendorff 1980/2004)
提出者Developed within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, FicoBernard Berelson; later systematised by Klaus Krippendorff
类型Quantitative observational research designQuantitative observational research method
开创性文献Riffe, D., Lacy, S., Watson, B., & Fico, F. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research (4th ed.). Routledge. ISBN: 9781138490536Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage. ISBN: 978-0761915454
别名longitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCAQCA, manifest content analysis, systematic content analysis, frequency-based content analysis
相关54
摘要Longitudinal quantitative content analysis systematically codes and counts features of texts, images, or media messages gathered at two or more points in time, enabling researchers to track how content changes, how themes rise or fall in prevalence, and how media or institutional messaging responds to external events. The design merges the structured measurement logic of quantitative content analysis with the temporal tracking power of longitudinal observation.Quantitative content analysis is a systematic, replicable method for converting the manifest content of text, images, or other recorded communication into numerical data. By applying a pre-specified codebook to a defined corpus and counting or scaling the resulting categories, researchers obtain frequency distributions, proportions, and relationships that can be subjected to standard statistical tests. It is the dominant method for large-scale, objective analysis of media, documents, social media posts, policy texts, and similar materials.
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ScholarGate方法对比: Longitudinal Quantitative Content Analysis · Quantitative Content Analysis. 于 2026-06-17 检索自 https://scholargate.app/zh/compare