Metaphor Identification in Large Texts Corpora by Yair Neuman, Dan Assaf, Yohai Cohen, Mark Last, Shlomo Argamon, Newton Howard, Ophir Frieder. (Neuman Y, Assaf D, Cohen Y, Last M, Argamon S, et al. (2013) Metaphor Identification in Large Texts Corpora. PLoS ONE 8(4): e62343. doi:10.1371/journal.pone.0062343)
Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpora of Reuters and the New York Times articles. The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms’ performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus.
A deep review of current work and promising new algorithms on metaphor identification.
I first saw this in Nat Torkinton’s Four short links: 14 May 2013.