{"title":"MSDIP: A Method for Coding Source Domains in Metaphor Analysis","authors":"W. Gudrun Reijnierse, Christian Burgers","doi":"10.1080/10926488.2023.2170753","DOIUrl":null,"url":null,"abstract":"This article describes the Metaphorical Source Domain Identification Procedure (MSDIP), which can be used to code source domains in metaphor identification. In the first part of the article, we describe the complexity of source-domain coding in corpus analysis. We argue that, in many cases, discourse is underspecified and multiple source-domain candidates may be relevant for a specific metaphorical expression. For instance, if a word like “fight” or “target” is used metaphorically, it could refer to either the source domain of war or sports. To make these issues explicit for analysts, we developed MSDIP, which builds on and extends the Metaphor Identification Procedure Vrije Universiteit (MIPVU). In the second part of the article, we explain the coding steps of MSDIP and subsequently report on a reliability analysis, demonstrating the reproducibility of the procedure. We end with a number of detailed sample analyses, demonstrating the role of co-text and context in selecting the likeliest source-domain candidate through MSDIP. These analyses show that MSDIP is both reliable and flexible in dealing with the complexities of real-life discourse during source-domain coding.","PeriodicalId":46492,"journal":{"name":"Metaphor and Symbol","volume":"6 1","pages":"0"},"PeriodicalIF":2.2000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metaphor and Symbol","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10926488.2023.2170753","RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 0
Abstract
This article describes the Metaphorical Source Domain Identification Procedure (MSDIP), which can be used to code source domains in metaphor identification. In the first part of the article, we describe the complexity of source-domain coding in corpus analysis. We argue that, in many cases, discourse is underspecified and multiple source-domain candidates may be relevant for a specific metaphorical expression. For instance, if a word like “fight” or “target” is used metaphorically, it could refer to either the source domain of war or sports. To make these issues explicit for analysts, we developed MSDIP, which builds on and extends the Metaphor Identification Procedure Vrije Universiteit (MIPVU). In the second part of the article, we explain the coding steps of MSDIP and subsequently report on a reliability analysis, demonstrating the reproducibility of the procedure. We end with a number of detailed sample analyses, demonstrating the role of co-text and context in selecting the likeliest source-domain candidate through MSDIP. These analyses show that MSDIP is both reliable and flexible in dealing with the complexities of real-life discourse during source-domain coding.
期刊介绍:
Metaphor and Symbol: A Quarterly Journal is an innovative, multidisciplinary journal dedicated to the study of metaphor and other figurative devices in language (e.g., metonymy, irony) and other expressive forms (e.g., gesture and bodily actions, artworks, music, multimodal media). The journal is interested in original, empirical, and theoretical research that incorporates psychological experimental studies, linguistic and corpus linguistic studies, cross-cultural/linguistic comparisons, computational modeling, philosophical analyzes, and literary/artistic interpretations. A common theme connecting published work in the journal is the examination of the interface of figurative language and expression with cognitive, bodily, and cultural experience; hence, the journal''s international editorial board is composed of scholars and experts in the fields of psychology, linguistics, philosophy, computer science, literature, and media studies.