Motifs: Dominant interaction patterns in event structures of serendipity

Introduction. This paper reports on research aimed at detecting motifs that take the form of interaction patterns found in event structures of serendipity. A motif is a frequently recurring theme, pattern or idea that appears within the bounds of a larger structure. Method. Fifty narratives recounting experiences of serendipity in research were analysed from an event-based perspective and described as networks of phenomenological event structures. Analysis. Motif detection is a form of statistical comparison that relies on the algorithmic generation of formal random network models. The Fast Network Motif Detection (FANMOD) software was employed to detect size 3 motifs containing ego occurring within the serendipity networks. Results. Four dominant motifs were detected: the exchange motif, the solo motif, the collaboration motif, and the chain motif. Each motif displayed distinct interaction and attribute patterning. Conclusions. The motif findings provide theoretical justification for the concept of normative interaction patterns in serendipity and support ideas relating to the importance of people and information in serendipity.