Digital story grammar: a quantitative methodology for narrative analysis

Digital story grammar (DSG) is a methodology that combines narrative theory and computerised text analysis. The methodology offers new ways of identifying patterns in narrative identity work and examining how these patterns relate to social structures such as gender and social class. DSG works through an algorithm that identifies narrative units consisting of subjects, verbs and objects. To demonstrate the potential of the methodology, we apply it to interviews with young people from the Timescapes Qualitative Longitudinal Data Archive and address four research questions: Who are in the young people’s stories (characters)? What are their narratives about (domains of experiences)? When do they taking place (temporality)? How are the narratives told (sense of agency)? Among other findings, we observed that young people with middle-class backgrounds convey a stronger sense of agency than their working-class peers, and we show how this correlates with the ways in which they navigate school-to-work trajectories.