Data Science and Intelligent Computing Techniques
Cracking the Figurative Code: A Survey of Metaphor Detection Techniques
Authors: Vrinda Kohli, Himanshu Nandanwar and Rahul Katarya
Publishing Date: 05-10-2023
ISBN: 978-81-955020-2-8
Abstract
Metaphor Detection is a crucial area of study in computational linguistics and natural language processing, as it enables the understanding and communication of abstract ideas through the use of concrete imagery. This survey paper aims to provide an overview of the current state-of-the-art approaches that tackle this issue and analyze trends in the domain across the years. The survey recapitulates the existing methodologies for metaphor detection, highlighting their key contributions and limitations. The methods are assigned three broad categories: feature-engineering-based, traditional deep learning-based, and transformer-based approaches. An analysis of the strengths and weaknesses of each category is showcased. Furthermore, the paper explores the annotated corpora that have been developed to facilitate the development and evaluation of metaphor detection models. By providing a comprehensive overview of the work already done and the research gaps present in pre-existing literature, this survey paper hopes to help future research endeavors, and thus contribute to the advancement of metaphor detection methodologies.
Keywords
Metaphor Detection, Natural Language Processing, Linguistic Analysis, Computational Linguistics, Lexical Semantics
Cite as
Vrinda Kohli, Himanshu Nandanwar and Rahul Katarya, "Cracking the Figurative Code: A Survey of Metaphor Detection Techniques", In: Satyasai Jagannath Nanda and Rajendra Prasad Yadav (eds), Data Science and Intelligent Computing Techniques, SCRS, India, 2023, pp. 347-359. https://doi.org/10.56155/978-81-955020-2-8-31