6,100 research outputs found

    Gradient Metaphoricity of the Preposition in: A Corpus-based Approach to Chinese Academic Writing in English

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    In Cognitive Linguistics, a conceptual metaphor is a systematic set of correspondences between two domains of experience (Kövecses 2020: 2). In order to have an extensive understanding of metaphors, metaphoricity (MĂŒller and Tag 2010; Dunn 2011; Jensen and Cuffari 2014; Nacey and Jensen 2017) has been emphasized to address one of the properties of metaphors in language usage: gradience (Hanks 2006; Dunn 2011, 2014), which indicates that metaphorical expressions can be measured. Despite many noteworthy contributions, studies of metaphoricity are often accused of subjectivity (MĂŒller 2008; Jensen and Cuffari 2014; Jensen 2017), this is why this study uses a big corpus as a database. Therefore, the main aim of this dissertation is to measure the gradient senses of the preposition in in an objective way, thus mapping the highly systematic semantic extension. Based on these gradient senses, the semantic and syntactic features of the preposition in produced by advanced Chinese English-major learners are investigated, combining quantitative and qualitative research methods. A quantitative analysis of the literal and other ten metaphorical senses of the preposition in is made at first. In accounting for the five factors influencing image schemata of each sense: “scale of Landmark”, “visibility”, “path”, “inclusion” and “boundary”, the formula of measuring the gradability of metaphorical degree is deduced: Metaphoricity=[[#Visibility] +[#Path] +[#Inclusion] +[#Boundary]]*[#Scale of Landmark]. The result is that the primary sense has the highest value:12, and all other extended senses have values down to zero. The more shared features with proto-scene, the higher the value of the metaphorical sense, and the less metaphorical the sense. EVENT and PERSON are the “least metaphoric” (value = 9-11); SITUATION, NUMBER, CONTENT and FIELD are “weak metaphoric” (value = 6-8); Also included are SEGMENTATION, TIME and MANNER (value = 3-5), and they are “strong metaphoric”; PURPOSE shares the least feature with proto-scene, and it has the lowest value, so it is “most metaphoric” (value = 0-2). Then, a corpus-based approach is employed, which offers a model for employing a corpus-based approach in Cognitive Linguistics. It compares two compiled sub-corpora: Chinese Master Academic Writing Corpus and Chinese Doctorate Academic Writing Corpus. The findings show that, on the semantic level, Chinese English-major students overuse in with a low level of metaphoricity, even advanced learners use the most metaphorical in rarely. In terms of syntactic behaviours, the most frequent nouns in [in+noun] construction are weakly metaphoric, whilst the nouns in the construction [in the noun of] are EVENT sense, which is least metaphorical. Moreover, action verbs tend to be used in the construction [verb+in] and [in doing sth.] in both master and doctorate groups. In the qualitative study, the divergent usages of the preposition in are explored. The preposition in is often substituted with other prepositions, such as on and at. The fundamental reason for the Chinese learners’ weakness is the negative transfer from their mother tongue (Wang 2001; Gong 2007; Zhang 2010). Although in and its Chinese equivalence zai...li (朹...里) share the same proto-scene, there are discrepancies: the metaphorical senses of the preposition in are TIME, PURPOSE, NUMBER, CONTENT, FIELD, EVENT, SITUATION, SEGMENTATION, MANNER, PERSON, while those of zai...li (朹...里) are only five: TIME, CONTENT, EVENT, SITUATION and PERSON. Thus the image schemata of each sense cannot be correspondingly mapped onto each other in different languages. This study also provides evidence for the universality and variation of spatial metaphors on the ground of cultural models. Philosophically, it supports the standpoint of Embodiment philosophy that abstract concepts are constructed on the basis of spatial metaphors that are grounded in the physical and cultural experience

    Deep Learning-Based Knowledge Injection for Metaphor Detection: A Comprehensive Review

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    The history of metaphor research also marks the evolution of knowledge infusion research. With the continued advancement of deep learning techniques in recent years, the natural language processing community has shown great interest in applying knowledge to successful results in metaphor recognition tasks. Although there has been a gradual increase in the number of approaches involving knowledge injection in the field of metaphor recognition, there is a lack of a complete review article on knowledge injection based approaches. Therefore, the goal of this paper is to provide a comprehensive review of research advances in the application of deep learning for knowledge injection in metaphor recognition tasks. In this paper, we systematically summarize and generalize the mainstream knowledge and knowledge injection principles, as well as review the datasets, evaluation metrics, and benchmark models used in metaphor recognition tasks. Finally, we explore the current issues facing knowledge injection methods and provide an outlook on future research directions.Comment: 15 page

    Directional adposition use in English, Swedish and Finnish

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    Directional adpositions such as to the left of describe where a Figure is in relation to a Ground. English and Swedish directional adpositions refer to the location of a Figure in relation to a Ground, whether both are static or in motion. In contrast, the Finnish directional adpositions edellĂ€ (in front of) and jĂ€ljessĂ€ (behind) solely describe the location of a moving Figure in relation to a moving Ground (Nikanne, 2003). When using directional adpositions, a frame of reference must be assumed for interpreting the meaning of directional adpositions. For example, the meaning of to the left of in English can be based on a relative (speaker or listener based) reference frame or an intrinsic (object based) reference frame (Levinson, 1996). When a Figure and a Ground are both in motion, it is possible for a Figure to be described as being behind or in front of the Ground, even if neither have intrinsic features. As shown by Walker (in preparation), there are good reasons to assume that in the latter case a motion based reference frame is involved. This means that if Finnish speakers would use edellĂ€ (in front of) and jĂ€ljessĂ€ (behind) more frequently in situations where both the Figure and Ground are in motion, a difference in reference frame use between Finnish on one hand and English and Swedish on the other could be expected. We asked native English, Swedish and Finnish speakers’ to select adpositions from a language specific list to describe the location of a Figure relative to a Ground when both were shown to be moving on a computer screen. We were interested in any differences between Finnish, English and Swedish speakers. All languages showed a predominant use of directional spatial adpositions referring to the lexical concepts TO THE LEFT OF, TO THE RIGHT OF, ABOVE and BELOW. There were no differences between the languages in directional adpositions use or reference frame use, including reference frame use based on motion. We conclude that despite differences in the grammars of the languages involved, and potential differences in reference frame system use, the three languages investigated encode Figure location in relation to Ground location in a similar way when both are in motion. Levinson, S. C. (1996). Frames of reference and Molyneux’s question: Crosslingiuistic evidence. In P. Bloom, M.A. Peterson, L. Nadel & M.F. Garrett (Eds.) Language and Space (pp.109-170). Massachusetts: MIT Press. Nikanne, U. (2003). How Finnish postpositions see the axis system. In E. van der Zee & J. Slack (Eds.), Representing direction in language and space. Oxford, UK: Oxford University Press. Walker, C. (in preparation). Motion encoding in language, the use of spatial locatives in a motion context. Unpublished doctoral dissertation, University of Lincoln, Lincoln. United Kingdo

    Static and dynamic metaphoricity in U.S.-China trade discourse:A transdisciplinary perspective

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    Metaphor scholars have widely explored metaphor use in political discourse. Nevertheless, the current research does not account for the ‘gradable metaphoricity’ in political discourse analysis. This dissertation fills this gap by addressing this specific issue in two frameworks: (1) viewing political metaphor from a static and gradient perspective (Source-Target mapping; Conventional vs. Novel vs. Dead), and (2) viewing political metaphor from a gradable and dynamic perspective (a matter of salience and awareness of metaphoricity). A systematic literature review in chapter 2 points out that the static and dynamic perspectives differ significantly in underlying assumptions and organizing principles, although both are indistinctly referred to by metaphor scholars as constituting a ‘gradable’ view. The former takes metaphor as a static conceptual unit or lexical unit, but the latter tends to accord a central role of activation of metaphoricity to metaphorical expressions. To launch a theoretical advancement about the dynamic view in political discourse, chapter 3 offers a usage-based model of gradable and dynamic metaphors—the YinYang Dynamics of Metaphoricity (YYDM). In addition, this thesis investigates political metaphors from an interdisciplinary angle, incorporating theory from the field of International Relations. An empirical evaluation of political (discourse) studies in chapter 4 shows the large absence of transdisciplinary perspectives. Addressing the abovementioned gaps, this dissertation reports on two empirical analyses of trade metaphors in a big corpus that represents the official trade positions of the United States and China during the presidencies of Bill Clinton and Jiang Zemin (1993-1997) as well as Donald Trump and Xi Jinping (2017-2021). Based on a codebook of a cross-linguistic metaphor identification procedure in chapter 5, the first empirical part contributes to the static and gradient perspective and includes two corpus-based studies of metaphorical framing about trade (chapters 6-7). The diachronic and cross-linguistic use of source domains from a socio-cognitive approach in chapter 6 reveals that source domains are semantic fields that vary with trade discourse contexts (interests, power, and power relations). Chapter 7 shows that the use of trade metaphors (source domains of Conventional and Novel metaphors) to construct and legitimize political ideologies correlates with differences between political genres. The second part contributes to the gradable and dynamic view by applying the transdisciplinary model of YinYang Dynamics of Metaphoricity in chapters 8-10. In chapter 8, an evaluation of the new model in the Clinton-Jiang trade discourse shows that the dynamic cognitive process (transformation of metaphoricity) and rhetorical process (argumentation and persuasion) mutually develop with the evolution of the socio-political process (trade perspectives and trade events). Chapter 9 investigates the transformation of metaphoricity in the Trump-Xi trade discourse and finds that cognitive processes (patterns of metaphoricity activation) and affective processes (emotions or sentiments) mutually develop with the evolution of socio-political processes (trade perspectives and trade events). Based on the findings in chapters 8-9, chapter 10 further shows several phenomena in the Clinton-Jiang and Trump-Xi trade discourses: the movement of metaphors on the metaphoricity spectrum, the bodily motivation of gradable and dynamic metaphoricity, and the interconnected political discourse systems. Drawing on all the theoretical and empirical insights revealed in the dissertation, the final section of the thesis outlines a future direction, i.e., moving towards a transdisciplinary and dynamic approach to metaphor in political discourse analysis

    Semantic radical consistency and character transparency effects in Chinese: an ERP study

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    BACKGROUND: This event-related potential (ERP) study aims to investigate the representation and temporal dynamics of Chinese orthography-to-semantics mappings by simultaneously manipulating character transparency and semantic radical consistency. Character components, referred to as radicals, make up the building blocks used dur...postprin

    A Survey on Semantic Processing Techniques

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    Semantic processing is a fundamental research domain in computational linguistics. In the era of powerful pre-trained language models and large language models, the advancement of research in this domain appears to be decelerating. However, the study of semantics is multi-dimensional in linguistics. The research depth and breadth of computational semantic processing can be largely improved with new technologies. In this survey, we analyzed five semantic processing tasks, e.g., word sense disambiguation, anaphora resolution, named entity recognition, concept extraction, and subjectivity detection. We study relevant theoretical research in these fields, advanced methods, and downstream applications. We connect the surveyed tasks with downstream applications because this may inspire future scholars to fuse these low-level semantic processing tasks with high-level natural language processing tasks. The review of theoretical research may also inspire new tasks and technologies in the semantic processing domain. Finally, we compare the different semantic processing techniques and summarize their technical trends, application trends, and future directions.Comment: Published at Information Fusion, Volume 101, 2024, 101988, ISSN 1566-2535. The equal contribution mark is missed in the published version due to the publication policies. Please contact Prof. Erik Cambria for detail
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