ADVANCING UNDERSTANDING THROUGH SEQUENCES: TRACING THE PATH OF SEQUENCE ANALYSIS IN SOCIAL SCIENCE RESEARCH

Abstract

This paper reflects on the progress of sequence analysis (SA) in the social sciences since its introduction four decades ago. The paper focuses on three main areas: (1) the origin and early growth of SA in the social sciences, the major developments, particularly those of the second-wave SA in the twenty-first century, with an examination of their strengths and limitations, and (3) possible future directions for SA. SA has witnessed significant applications in the social sciences, particularly in life course research, over the last two decades. The exponential increase in results containing the terms "sequence analysis" and "life course" demonstrates the growing popularity of SA. This paper presents a detailed yearly growth trend of SA and uses a life course analogy to explore the different stages of its development.

The paper introduces a typical application of SA involving coding narratives or processes as sequences, measuring pairwise dissimilarities between sequences, and data reduction through cluster analysis. It highlights the importance of considering regularities in sequencing, timing, and duration when comparing sequences. The choice of criterion for comparing sequence similarities should align with the research question at hand. The paper also discusses various dissimilarity-based analytical tools, such as identifying representative sequences and measuring sequence discrepancy.

In subsequent sections, the paper delves into the birth of SA in the 1980s and provides historical context. It then presents a comprehensive review of methodological developments in SA, covering visualization, complexity measures, dissimilarity measures, group analysis, cluster analysis, multidomain/multichannel SA, dyadic/polyadic SA, Markov chain SA, sequence life course analysis, sequence network analysis, SA in other social science research, and software for SA