Topic summary
Social sequence analysis

Extracted from the Wikipedia article Sequence analysis in social sciences.
History
Many of the methodological developments in sequence analysis came on the heels of a special section devoted to the topic in a 2000 issue of Sociological Methods & Research, which hosted a debate over the use of the optimal matching (OM) edit distance for comparing sequences. In particular, sociologists objected to the descriptive and data-reducing orientation of optimal matching, as well as to a lack of fit between bioinformatic sequence methods and uniquely social phenomena. The debate has given rise to several methodological innovations (see Pairwise dissimilarities below) that address limitations of early sequence comparison methods developed in the 20th century. In 2006, David Stark and Balazs Vedres proposed the term "social sequence analysis" to distinguish the approach from bioinformatic sequence analysis. However, if we except the nice book by Benjamin Cornwell, the term was seldom used, probably because the context prevents any confusion in the SA literature. Sociological Methods & Research organized a special issue on sequence analysis in 2010, leading to what Aisenbrey and Fasang referred to as the "second wave of sequence analysis", which mainly extended optimal matching and introduced other techniques to compare sequences. Alongside sequence comparison, recent advances in SA concerned among others the visualization of sets of sequence data, the measure and analysis of the discrepancy of sequences, the identification of representative sequences, and the development of summary indicators of individual sequences. Raab and Struffolino have conceived more recent advances as the third wave of sequence analysis. This wave is largely characterized by the effort of bringing together the stochastic and the algorithmic modeling culture by jointly applying SA with more established methods such as analysis of variance, event history analysis, Markovian modeling, social network analysis, or causal analysis and statistical modeling in general.