Metaphor-based Multi-Dimensional Approach and Register Analysis

Metaphor-based Multi-Dimensional Approach and Register Analysis was successfully held on Tencent Meeting at 14:00 on April 17th, 2020. The lecture was delivered by Prof. Sun Ya, doctoral supervisor of School of International Studies, University of International Business and Economics, and was hosted by Prof. Yang Zi from the School of Foreign Studies (the SFS), University of Science and Technology Beijing (USTB), with over 30 teachers and graduate students attended.

Prof. Sun gave a detailed interpretation on the study from many aspects— research foundations, corpora, questions, methods, processes, and conclusions.

Prof. Sun started by explaining the definition of metaphor and register analysis and their relationship. In this process, he mentioned that Multi-Dimensional Approach (MDA) is a common method used for register analysis and metaphor is one of the typical language features of semantic analysis. Based on 2 business corpora, the observed corpus (materials: missions, visions and strategies on English websites of Fortune 500 companies in China and the United States) and the reference corpus (materials: the subset of Business English Corpus), prof. Sun mainly discussed 3 questions— first, on the base of MDA, which kind of register type should the observed corpus be classified into and what are the dimensional and linguistic features of observed corpus? Second, how can we determine the variables of Multi-Dimensional Approach (M-MDA) and what are the dimensional features of observed corpus based on M-MDA? Third, what are the advantages of M-MDA over MDA?

As MDA mainly takes syntactic features into consideration and relatively ignores semantic features, hence resulting in an inadequate semantic analysis, Prof. Sun took an innovative method, Metaphor-based Multi-Dimensional Approach (M-MDA), to conduct the research. In order to make a comparison, he first adopted MDA to analyze the register type, dimensional and linguistic features of the 2 corpora. Then based on M-MDA, he conducted a factor analysis of register-specific metaphor’s semantic and syntactic features by making references to Biber’s Multi-Dimensional steps.

Results based on MDA revealed that the observed corpus’s register type is academic expository text and the reference corpus’s is persuasive text; classified by dimensional features, observed corpus is information expressive discourse while the referents in the corpus are explicit; language features can be classified into negative features shown by nouns, verbs, qualitative and attributive adjectives and positive features shown by relative clauses guided by wh-words, preposition pied-piping, clauses coordinate structure phrases and nominalized phrases.

Results based on M-MDA indicated that from dimension I, II and III, the corpus is respectively an information expression based on the metaphors of character movement, a non-narrative expression based on the metaphors of object enlargement, and an information expression based on the metaphors of object orientation.

Comparing the above research results, Prof. Sun summarized the advantages of M-MDA. First, M-MDA supports MDA’s findings: the main communicative function of observed corpus is informative expression, and metaphor is the distinctive feature of register. Moreover, it supplements MDA’s findings: MDA’s variables are all syntactic variables, which only supports that observed corpus is an informative expression but fails to reveal the specific content of the communicative purpose, while M-MDA can further explain its informative content. In addition, M-MDA reveals the relationship between the semantic features of the source domain and forms the basic structure of metaphors.

Finally, Prof. Sun enthusiastically answered relevant questions raised by teachers and students. The lecture wins a great success in that it not only provides students with a preliminary understanding of the corpus-based cognitive linguistics research, but also expands students’ horizons of metaphor research.

Contributor: Zong Mingxia