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感知诗意世界:诗歌漫画的语料库辅助及物性分析

Perceiving the poetic world: A corpus-assisted transitivity analysis of poetry comics.

作者信息

Chen Shukun, Zhong Zenan

机构信息

School of Foreign Languages and Cultures, Guangdong University of Finance, Guangzhou, China.

出版信息

Front Psychol. 2022 Dec 28;13:1061169. doi: 10.3389/fpsyg.2022.1061169. eCollection 2022.

Abstract

While modern adaptations of Chinese classics have drawn keen scholarly interests lately, the comic adaptation of Chinese traditional poetry remains under-investigated. Extending the previous research on intersemiotic translation and comics, this paper, drawing on the analytical framework of systemic functional semiotics, examines distribution of process types of language in poems in comparison with that in comic images in the exemplary case drawn by Cai Zhizhong, using UAM image as the annotation tool. The comic book formulates a multimodal corpus that consists of 1,097 clauses and 605 images. We have manually analyzed the process type of the poems and their corresponding comic panels. Our quantitative and qualitative results show that there are distinct patterns of process-type distributions between verbal poems and images. Poems have been turned into perceptions, actions, and verbal processes in comic strips, which serve various purposes such as construction of the poet's gaze, relations building, storyline development, dramatization, metaphor visualization, etc. The paper is concluded with discussion on how the intersemiotic translation of poems might produce effects on readers.

摘要

虽然近年来中国经典的现代改编引发了学者们的浓厚兴趣,但中国传统诗歌的漫画改编仍未得到充分研究。本文在之前关于跨符号翻译和漫画的研究基础上,借鉴系统功能符号学的分析框架,以蔡志忠绘制的典型案例为样本,使用UAM图像作为注释工具,对比诗歌与漫画图像中语言的过程类型分布。该漫画书构成了一个多模态语料库,包含1097个小句和605幅图像。我们手动分析了诗歌及其对应的漫画面板的过程类型。我们的定量和定性结果表明,文字诗歌和图像之间存在不同的过程类型分布模式。诗歌在漫画中被转化为感知、行动和言语过程,服务于多种目的,如构建诗人的视角、建立关系、发展故事情节、戏剧化、隐喻可视化等。文章最后讨论了诗歌的跨符号翻译可能对读者产生的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91ba/9835094/ecfaeb84f2cf/fpsyg-13-1061169-g001.jpg

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引用本文的文献

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本文引用的文献

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Not so secret agents: Event-related potentials to semantic roles in visual event comprehension.
Brain Cogn. 2017 Dec;119:1-9. doi: 10.1016/j.bandc.2017.09.001. Epub 2017 Sep 9.
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