Synchronising Sequences. An Analytic Approach to Explore Relationships Between Events and Temporal Patterns View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

Denis Colombi , Simon Paye

ABSTRACT

Sequence data is most of the time analysed in calendar time (historical periods, daily schedules) or in age-based process time. However, many social processes unfold according to event-related time patterns and need other time references to be studied. This chapter presents a simple analytical operation, called sequence synchronisation, which allows studying social processes that are strongly linked to specific events. It consists in defining the time axis of the sequences according to the time preceding or elapsed after a specific event. The event chosen for synchronising sequence data can be either endogenous or exogenous to the sequence alphabet. Two empirical case studies are presented in order to support the usefulness of sequence synchronisation: the analysis of functional differentiation within the academic profession, and a study of class mobility of French back-migrants. The strengths and weaknesses of sequence synchronisation are assessed against three different methods: event history analysis, multichannel sequence analysis and multiple sequence alignment. Sequence synchronisation appears as a simple and efficient means to study the interaction between events and temporal patterns, and provides interesting opportunities to operationalise the concepts of turning point and differentiation using sequence data. More... »

PAGES

249-264

Book

TITLE

Advances in Sequence Analysis: Theory, Method, Applications

ISBN

978-3-319-04968-7
978-3-319-04969-4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-04969-4_13

DOI

http://dx.doi.org/10.1007/978-3-319-04969-4_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042458257


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