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Optimal Matching Analysis×Relational Event Model×
분야SociologySociology
계열Process / pipelineRegression model
기원 연도1970 (algorithm); 1980s (sociology)2008
창시자Needleman & Wunsch (algorithm); Andrew Abbott (sociological use)Carter T. Butts
유형Edit-distance dissimilarity between categorical sequencesEvent-history model for time-stamped relational events
원전Abbott, A., & Tsay, A. (2000). Sequence analysis and optimal matching methods in sociology: review and prospect. Sociological Methods & Research, 29(1), 3–33. DOI ↗Butts, C. T. (2008). A relational event framework for social action. Sociological Methodology, 38(1), 155–200. DOI ↗
별칭optimal matching, OMA, edit-distance sequence comparison, Levenshtein sequence distanceREM, relational event framework, dynamic network event model, event-history network model
관련54
요약Optimal matching analysis measures how dissimilar two categorical sequences are by computing the minimum total cost of editing one sequence into the other through substitution and insertion/deletion operations. Borrowed from computer science and molecular biology and introduced to sociology by Andrew Abbott, it supplies the pairwise distances that underpin sequence analysis of careers, family histories, and other life-course trajectories.The relational event model (REM), introduced by Carter Butts in 2008, analyzes streams of time-stamped interactions — emails, radio calls, messages, citations — as a continuous-time event-history process. Rather than treating a network as a static set of ties, it models the instantaneous rate at which any sender directs an action at any receiver as a function of the history of past events, letting researchers test how prior interaction shapes future interaction.
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