Social sequence analysis

Social sequence analysis is a special application of sequence analysis, a set of methods that were originally designed in bioinformatics to analyze DNA, RNA, and peptide sequences. Social sequence analysis involves the examination of ordered social processes, ranging from microsocial interaction patterns (for example, turn-taking dynamics in conversations) and interpersonal contact dynamics to the development of social hierarchies and macrosocial temporal patterns. The analysis of such patterns can involve descriptive accounts of sequence patterns, statistical event history analysis, optimal matching analysis, narrative or event structure analysis, and dynamic social network sequencing. After being introduced to the social sciences in the 1980s and a period of slow growth during the 1990s, social sequence methods have become increasingly prevalent.Sequence analysis methods were first imported into the social sciences from the biological sciences 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, and especially sociology have been using sequence methods ever since.The analysis of social sequence patterns has foundations in sociological theories that emerged in the middle of the 20th century. Structural theorists argued that society is a system that is characterized by regular patterns. Even seemingly trivial social phenomena are ordered in highly predictable ways. This idea serves as an implicit motivation behind social sequence analysts’ use of optimal matching, clustering, and related methods to identify common “classes” of sequences at all levels of social organization, a form of pattern search. This focus on regularized patterns of social action has become an increasingly influential framework for understanding microsocial interaction and contact sequences, or “microsequences.” This is closely related to Anthony Giddens’s theory of structuration, which holds that social actors’ behaviors are predominantly structured by routines, and which in turn provides predictability and a sense of stability in an otherwise chaotic and rapidly moving social world. This idea is also echoed in Pierre Bourdieu’s concept of habitus, which emphasizes the emergence and influence of stable worldviews in guiding everyday action and thus produce predictable, orderly sequences of behavior. The resulting influence of routine as a structuring influence on social phenomena was first illustrated empirically by Pitirim Sorokin, who led a 1939 study that found that daily life is so routinized that a given person is able to predict with about 75% accuracy how much time they will spend doing certain things the following day. Talcott Parsons’s argument that all social actors are mutually oriented to their larger social systems (for example, their family and larger community) through social roles also underlies social sequence analysts’ interest in the linkages that exist between different social actors’ schedules and ordered experiences, which has given rise to a considerable body of work on synchronization between social actors and their social contacts and larger communities. All of these theoretical orientations together warrant critiques of the general linear model of social reality, which as applied in most work implies that society is either static or that it is highly stochastic in a manner that conforms to Markov processes. This concern inspired the initial framing of social sequence analysis as an antidote to general linear models. It has also motivated recent attempts to model sequences of activities or events in terms as elements that link social actors in non-linear network structures. This work, in turn, is rooted in Georg Simmel’s theory that experiencing similar activities, experiences, and statuses serves as a link between social actors.Sequence analysis techniques are increasingly used to study a wide variety of sequenced, or ordered, social phenomena. Sequences usually refer to phenomena that are ordered temporally (that is, involving events or states that unfold over a period of time), but a sequence may also reflect spatial order, preference order, hierarchical order, logical order, or other types of order. A variety of techniques have been designed to describe, quantify, and predict these orders.The first international conference dedicated to social-scientific research that uses sequence analysis methods – the Lausanne Conference on Sequence Analysis , or LaCOSA – was held in Lausanne, Switzerland in June 2012. A second conference (LaCOSA II) was held in Lausanne in June 2016. Future international conferences will be held every two years in different locations.