Activity Pattern Analysis by Means of Sequence-Alignment Methods

Abstract

The author describes a method of comparing sequences of characters, called sequence alignment or string matching, and illustrates its use in the analysis of daily activity patterns derived from time-use diaries. It allows definition of measures of similarity or distance between complete sequences, called global alignment, or the evaluation of the best fit of short sequences within long sequences, called local alignment. Alignments may be done pairwise to develop similarity or distance matrices that describe the relatedness of individuals in the set of sequences being examined. Pairwise alignment methods may be extended to many individuals by using multiple alignment analysis. A number of elementary hand-worked examples are provided. The basic concepts are discussed in terms of the problems of time-use research and the method is illustrated by examining diary data from a survey conducted in Reading, England. The CLUSTAL software used for the alignments was written for molecular biological research. The method offers a powerful technique for analyzing the full richness of diary data without discarding the details of episode ordering, duration, or transition. It is also possible to extend the analysis to include the context of activities, such as the presence of other persons or the location, but such extensions would require software designed for social science rather than biochemical problems. The method also offers a challenge to researchers to begin to develop theories about the determinants of daily behavior as a whole, rather than about participation in single activities or about time-budget totals.