The Automatic Identification of Conceptual Metaphors in Hungarian Texts: A Corpus-Based Analysis

The present study is a corpus-based analysis of literal versus metaphorical language use. Previous corpus linguistic works have focused on the linguistic characteristics of the metaphorical expressions. The main question of the present paper is whether the automatic identification of certain conceptual metaphors could be successful taking the embodiment hypothesis as a starting point. 12 widespread conceptual metaphors were selected from Lakoff & Johnson (1980) and the metaphor index in Kovecses (2002), where consistent mapping was observed between a concrete (source) domain and an abstract (target) domain. According to our hypothesis, a metaphoric sentence should include both source-domain and target-domain expressions. This assumption was tested relying on three different methods of selecting target-domain and source-domain expressions: a psycholinguistic word association method, a dictionary method and a corpus-based method. The results show that for the automatic identification of metaphorical expressions, the corpus-based method is the most effective strategy, which suggests that the concept of source and target domains is best characterized by statistical patterns rather than by psycholinguistic factors.