Semantic Analysis of Migrants’ Self-entrepreneurship Ecosystem Narratives

NooJ represents a powerful tool for discourse analysis, and promises great developments in the interpretation of articulate concepts across texts. In spite of the software’s ability to integrate syntactic operations in text parsing, social scientists seldom use NooJ for large discourse analysis procedures, leaving NooJ-powered discourse analysis protocols largely underdeveloped. This study chiefly aims to establish an early discourse analysis canon for NooJ analysts to use in social science research, in particular, sociolinguistics. We identified migrant self-entrepreneurship as a subject of study, and investigated its conceptual development across seven separate interviews with aspiring migrant entrepreneurs. Our data collection primarily consisted of semi-structured interviews, which we conducted in anticipation of NooJ-powered co-occurrence analysis. This article offers insights into research best practices we recommend researchers to employ when conducting co-occurrence analysis, with special regard to congruence patterns, overlapping expressions, divergence patterns and low occurrences. In conclusion, this study comes as a demonstration that NooJ is a perfect fit for a form of scientific text interpretation that goes beyond well-established thematic analysis techniques in terms of representational insightfulness and analytical depth. Importantly, NooJ-powered discourse analysis makes it possible to aid qualitative methods with quantitative assessments, ushering promising developments in computational sociolinguistics. We see this publication as a possible first step for NooJ-powered analysis to new sociolinguistic pursuits and for its affiliated scientific community to study social phenomena with novel depth.