In social sciences, sequence analysis (SA) is concerned with the analysis of sets of categorical sequences that typically describe longitudinal data. Analyzed sequences are encoded representations of, for example, individual life trajectories such as family formation, school to work transitions, working careers, but they may also describe daily or weekly time use or represent the evolution of observed or self-reported health, of political behaviors, or the development stages of organizations. Such sequences are chronologically ordered unlike words or DNA sequences for example.
SA is a longitudinal analysis approach that is holistic in the sense that it considers each sequence as a whole. SA is essentially exploratory. Broadly, SA provides a comprehensible overall picture of sets of sequences with the objective of characterizing the structure of the set of sequences, finding the salient characteristics of groups, identifying typical paths, comparing groups, and more generally studying how the sequences are related to covariates such as sex, birth cohort, or social origin.
Introduced in the social sciences in the 80s by Andrew Abbott, SA has gained much popularity after the release of dedicated software such as the SQ and SADI addons for Stata and the TraMineR R package with its companions TraMineRextras and WeightedCluster.
Despite some connections, the aims and methods of SA in social sciences strongly differ from those of sequence analysis in bioinformatics.
History
Sequence analysis methods were first imported into the social sciences from the information and biological sciences (see Sequence alignment) by the University of Chicago sociologist Andrew Abbott in the 1980s, and they have since developed in ways that are unique to the social sciences. Scholars in psychology, economics, anthropology, demography, communication, political science, organizational studies, and especially sociology have been using sequence methods ever since.
In sociology, sequence techniques are most commonly employed in studies of patterns of life-course development, cycles, and life histories. There has been a great deal of work on the sequential development of careers, and there is increasing interest in how career trajectories intertwine with life-course sequences. Many scholars have used sequence techniques to model how work and family activities are linked in household divisions of labor and the problem of schedule synchronization within families. The study of interaction patterns is increasingly centered on sequential concepts, such as turn-taking, the predominance of reciprocal utterances, and the strategic solicitation of preferred types of responses (see Conversation Analysis). Social network analysts (see Social network analysis) have begun to turn to sequence methods and concepts to understand how social contacts and activities are enacted in real time, and to model and depict how whole networks evolve. Social network epidemiologists have begun to examine social contact sequencing to better understand the spread of disease. Psychologists have used those methods to study how the order of information affects learning, and to identify structure in interactions between individuals (see Sequence learning).