Network analysis examines the pattern of relationships between causal factors and the focal event to provide a model of the perceived causal structure. Its application to modelling perceptions of causality in psychology was pioneered by Lunt’s (1988) examination of perceived causes of examination failure subsequently it has addressed a broad range of research questions in various psychological disciplines. Network analysis comprises various techniques for examining both how people structure their causal beliefs and the extent to which the causal understanding is shared amongst individuals (Reser & Muncer, 2004). Network theory offers a broad framework to productively examine complex systems across disciplines Barabási (2012) argues that theories cannot ignore the network effects caused by interconnectedness. Dedicated journals and conferences testify to the importance of network analysis: notably, network analysis was a programme theme at the 2011 American Psychological Society conference.

Borgatti et al., 2009) research has examined fundamental psychological constructs such as intelligence (van Geert, 1998) and personality in terms of dynamic network systems (e.g.

The growing interest in interconnectedness is salient for psychology as networks pervade all aspects of human psychology (e.g. Complex causal attributions require connected attributes that have sophisticated dynamic pathways of action between them such connections form networks, and network science offers novel theoretical tools and techniques How do we make sense of the causes of events? Psychologists have long puzzled over this question, and increasingly researchers are availing of developments in network science to understand the complexity of our causal thinking.

Network analysis definition