Metaphor and the Social World 1:2 (2011), 174–201. doi 10.1075/msw.1.2.04dor issn 2210–4070 / e-issn 2210–4097 © John Benjamins Publishing Company Recognition of personiications in iction by non-expert readers Aletta G. Dorst, Gerben Mulder and Gerard J. Steen Faculty of Arts, VU University Amsterdam his paper ofers an integrated typology for the classiication of personiications in discourse, based on existing methods for linguistic metaphor identiication such as MIP (Pragglejaz Group, 2007) and MIPVU (Steen et al., 2010). he psychological relevance of the proposed typology is explored in an empirical study that examines the recognition of personiications in iction by non-expert readers. A selection of structural properties of personiications is discussed and predictions are formulated regarding which values of which variables are deemed to boost the recognition of personiications. he results suggest that the diferent types of personiication difer in recognizability and that their recogni- tion may be more strongly determined by inherent properties (such as conven- tionality) than by external factors (such as the presence of a prime). hough the results cannot be unambiguously interpreted, they do indicate some tendencies in the behaviour of non-expert readers and their perceptions of the forms and functions of personiication in iction. Keywords: personiication types, personiication properties, personiication recognition, iction 1. Introduction Since Lakof and Johnson (1980) showed that metaphor is ubiquitous in language and thought, one major concern in the ield of metaphor research has been the reliable identiication and analysis of metaphoric language in naturally occur- ring data rather than isolated constructed examples. he recent publications of the Metaphor Identiication Procedure (MIP) and its extended version developed by the VU University team MIPVU (Steen et al., 2010) have demonstrated that it is possible to have a reliable procedure for linguistic metaphor identiication. However, the application of MIPVU to a corpus of some 190,000 words from four