1 Introduction
1.1 Research Background
Metaphor is used to describe the metaphorical meaning of words in order tobetter understand the concept. Concept is at the heart of our understanding of theworld. Metaphors are that structure of how we perceive, how we think, and what wedo. Our conceptualization of the world takes place through metaphor[1-2]. Metaphorconstruction often appears in academic discourse. Academic discourse guides themaking of academic meanings[3], where words are used to refer to concepts morespecifically than in ordinary usage[4]. Thus, lexical metaphor plays an important rolein the abstract meaning of metaphor in academic discourse. Meanwhile, grammaticalmetaphor within the ideational metafunction also involves a re-mapping betweensequences, figures and elements in the semantics and clause nexuses, clauses andgroups in the grammar[5]. Grammatical metaphor expresses the objectivity,concentration, information density, technicality and rationality of academicdiscourse[6]. Therefore, grammatical metaphor is of great significance for studying thegrammatical realization of metaphor.
Characterization of thematic items is important for the increased understandingof interdisciplinary metaphor construction, since thematic items, for example, keyparticipants or concepts, may regularly fulfil certain roles in the texts studies[4].Learning has been an important concept in the study of the language learning andmachine learning. With the construction of One Belt and One Road were continuallypromoted, it is hoped that reinforcement of learners’ English learning, improvementof their English proficiency and their communication ability will provide anopportunity to transfer dominant industries and develop international markets.Machine learning, as a sub-field of artificial intelligence research, is increasinglyrecognized as a worldwide technological concern[7]. In this study, a corpus-basedcomparative study is conducted, systematically investigating metaphor construction ofthematic item learning in academic discourse of applied linguistics and computerscience.
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1.2 Research Questions
Based on a comparative study, this study investigates metaphor construction oflearning from metaphorical variation of meaning and its grammatical realization inthe field of applied linguistics and computer science. The following questions areaddressed.
(1) How is learning metaphor realized lexically in applied linguistics discourseand computer science discourse？
(2) How is learning metaphor realized grammatically in applied linguisticsdiscourse and computer science discourse？Congruently or incongruently?
(3) Are there any differences of learning metaphor construction between appliedlinguistics discourse and computer science discourse？
(4) What are the factors that affect the construction of learning metaphor inapplied linguistics discourse and computer science discourse?
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2 Literature Review
2.1 Metaphor
2.1.1 Definition of Metaphor
In cognitive linguistics, as a means of creating new ideologies, metaphor refersto the metaphor transferring from the source domain to the target domain[2,8]. In SFG,the term of metaphor traditionally applied to the lexical transformation which can bedescribed as variation in the use of words[9]. It is described as variation in the use ofwords: a word is said to be used with a transferred meaning which is realized by aselection of words that is different from the typical meaning[10]. It is seen as relating tothe way a particular word is used, and the term metaphorical is used as the opposite ofliteral, to describe the meaning of the word[11]. Actually, there is no essentialdifference between the definitions of metaphor in the two domains. The metaphor isin our very concept of an argument and is helpful to understand complex ideas andconcepts in academic discourse.
2.1.2 Metaphor Construction in Academic Discourse
Discourse is regarded as organized bodies of knowledge and practice which areboth enabling and constraining, i.e., it includes disciplinary knowledge anddisciplinary practice[12]. Academic discourse can be pided into natural sciencediscourse and social science discourse. Natural science involves trying to understandthe world by looking at it through a technical framework: turning commonsenseunderstandings into technical understandings[12]. Natural science discourse creates atechnical language through setting up technical terms, arranging those termstaxonomically and then using that framework to explain how the world came to be asit is. The discourse of social science will be shown to contain features of both scienceand the humanities, leading to particular kinds of complexity at the level ofgrammatical metaphor. Social science takes its starting point as an abstract construalof experience and then reconstrues that initial abstraction technically[12].
Metaphor construction in academic discourse focuses on the thematic items, andcan be studied from three approaches, i.e., lexical metaphor, grammatical metaphorand lexicogrammatical metaphor. In the process of studying academic meaning, thestarting point is the system of meaning, especially the selection of the system ofinterpretation (genre), which guides the formation of academic meaning[3].
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2.2 Lexical Metaphor
2.2.1 Definition of Lexical Metaphor
Lexical metaphor constitutes a form of referential indirectness or incongruitywhich has been typically used in cognitive linguistics. Referential indirectness andincongruity pertain to metaphorical language use in the sense that terms are used inother senses than their basic senses[13]. Lexical metaphor, as a means of creating newideologies, refers to the metaphor transferring from the source domain to the targetdomain as in Argument is war[14] (Tab. 2.1).
语言学论文怎么写
SFG have accepted that the cognitive linguistics notion of metaphor as aconceptual cross-domain mapping may provide a unifying platform for the descriptionof both grammatical as well as what they call lexical metaphor[15]. In the same vein,lexical metaphor in SFG typically involves a transfer from a more concrete donordomain into a more abstract domain, so that abstract concepts come to beconceptualized in more concrete terms. Metaphor transferring from the source domainto the target domain as in Time is a journey[2], is called lexical metaphor. According toHalliday[16], with lexical metaphors, within a given field, this seems unproblematic: aword’s basic meaning in that field is taken as literal. Transferred readings are thenderived by taking the term’s collocational and colligational context into account. Inpractical terms, dictionaries can be used to determine the basic meaning of a lexicalitem being used metaphorically. In this sense, a lexeme with a certain literal meaningcan have metaphorical, transferred uses or meanings. The expression a flood ofprotests poured in is a good illustration of lexical metaphor[9], where the verb flood,usually associated with rivers, is transferred to refer to protests (Tab. 2.2).
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3 Theoretical Framework..................................... 16
3.1 Metaphorical Variation of Meaning................................. 16
3.2 Grammatical Realization of Metaphor...................................18
4 Methodology.................................... 22
4.1 Corpus Compilation....................................... 22
4.2 Identification of Learning Metaphor...........................22
5 Results.................................. 27
5.1 Metaphorical Variation of Learning Metaphor.............................. 27
5.1.1 Learning Metaphor in LL Corpus................................ 27
5.1.2 Learning Metaphor in ML Corpus.................................... 31
6 Discussion
6.1 Comparison at the Lexical Level
Results show that Learning metaphor appeared 145 and 142 tokens respectivelyin LL corpus and ML corpus, and there were 35 and 36 types respectively. Allanalyses were carried out using SPSS, version 25. Tab. 6.1 shows the analysis resultsof the chi-square test, and illustrates that categories of Learning is process andLearning is method in the two corpora have significant differences in the number oftokens. There is significant difference between the two corpora in terms of Learningis education and Learning is war. Since the metaphor of Learning is journey was notfound in ML corpus, the chi-square test was not carried out. However, the Learning isjourney metaphor frequently occurred in LL corpus, hence, it can be concluded thatthis kind of war metaphor appears more frequently in the field of applied linguistics.It is worth noting that there is no significant difference in the number of tokensbetween the two corpora in terms of Learning is entertainment and Learning isbuilding, which proves that these two kinds of learning metaphor are used similarly inapplied linguistics and computer science.
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7 Conclusion
7.1 Major Findings
The first question in this study sought to determine learning metaphor and itsdifferences at the lexical level between applied linguistics discourse and computerscience discourse. From the perspective of lexical metaphor, this paper summed uptwo different metaphors, i.e., Learning is process metaphor in applied linguistics andLearning is method metaphor in computer science, which illustrated thecharacteristics of the two disciplines and experience, the influence of the metaphor’sdifferent mappings between source domain and target domain. This study also foundthat there was no significant difference in the numbers of metaphors under the typesof two branches, which to some extent proves that Learning is method metaphorcannot be seen as a new metaphor, and the metaphorical construction of learning stillappeared more frequently in applied linguistics. However, the frequency of Learningis education metaphor and Learning is journey metaphor in LL corpus wassignificantly higher than that in ML corpus respectively, which is mainly becausehuman beings are more closely related to education and journey, so these two types ofmetaphors had a higher degree of similarity and were used more frequently in appliedlinguistics. However, Learning is war metaphor has a stronger correspondence withthe goals and strategies in war, so this metaphor was more commonly used in the fieldof computer science.
The second obvious finding to emerge from the analysis was the congruent andincongruent grammatical realization forms of learning metaphor. It was found that inapplied linguistics and computer science, learning metaphor mainly depended oncongruent realization and all verbs took the congruent form in both disciplines. Butthere were more incongruent forms of nouns and adjectives in computer science thanin applied linguistics. Considering the branches of learning metaphor, this study didnot find any differences of nominalization in two disciplines, but there weredifferences of adjectivization between branches of learning metaphor. Adjectivizationof metaphors Learning is education, Learning is entertainment and Learning is warappeared more frequently in computer science discourse, while adjectivization ofLearning is building metaphor appeared more frequently in applied linguistics.
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