A Digital Humanities Approach To Representation And Reconstruction Of Affect Meaning In Chinese Versions Of Gone With The Wind

Since the 21 st century,“Digital Humanities(DH)”,originating from “humanistic computing”,is a brand-new methodology integrating computing and humanities.It provides a new research paradigm and rich research perspective for the traditional humanities and facilitates access for the humanities to obtain data and discover problems.It has become a highlight of academic circles and a growth pole of scholarly publications.Digital Humanities(DH)research has given birth to a close and distant reading(CDR)by a mutually supportive combination of traditional close reading and distant reading(CDR),involving corpus-linguistic analysis and text visualization.Translation studies in DH have made available innovative approaches to scholars concerned,broadening the scope of humanities research.It brings the thinking and methods of scientific research based on computer and digital humanities tools,including corpus,and gives full play to the subjectivity and initiative of traditional humanities.This study takes the theories and methodologies of Appraisal Theory and Corpus Translation Studies as guidance and draws on the research results of the DH research paradigm for translation studies and corpus stylistics.On the groundwork of the selfbuilt 1 to 9 English-Chinese parallel corpus of Gone with the Wind(GWTW)and the self-built corpus of famous American novels and the general corpora as the reference,the study aims to investigate the following aspects by leveraging the respective advantages of AI-based sentiment analysis technology,visualization technology,and corpus technology:1.Distant reading of GWTW and its versions,and their text data mining and text analysis;2.Building the analytical framework of the novel’s affective connotations in the digital humanistic perspective under the theoretical framework of the Affect System of Appraisal Theory;3.Exploring how well translators sense the affective elements and meanings in the source language and achieve ideal affective validity of the versions corresponding to the source text(ST)’s affective connotations in terms of macro-quantitative analysis of affect categories,affective word density/ intensity,affective valence,and affective flow,the reproduction of affective connotations at the lexico-grammatical level,and the reproduction of the narrative function of affective words.4.On these bases,the factors affecting the translator’s emotional involvement are examined,and the emotional translation strategies adopted by the translator are summarized.The main research questions of this study include five aspects:1.What are the macro-linguistic features of the ST and the nine target texts(TTs)? What are the differences between ST and TTs,and TTs?2.What are the differences between the versions regarding affect categories,affect word density/intensity,affective valence,and affective flow?3.How do the affective connotations of the nine versions achieve affective equivalence with those in the ST text at the lexico-grammatical level? What are the specific differences?4.How do the characterization and narrative functions of the affect words in the nine versions achieve optimal affective equivalence by representation and reconstruction of affective meanings to those in the ST? What are the specific differences?5.What are the translator’s factors regarding emotional involvement in translating? What are affective translation strategies?Major findings are as follows:1.With the help of DH “distant reading” technology,we can quickly and intuitively understand the text information of GWTW,the information of each main character,high-frequency affect words,keywords of the character image,and the intimacy of character relationships.Using multidimensional analysis,we found that GWTW belongs to the Imaginative Narrative genre,typically characterized by a strong narrative.The vocabulary richness is higher than that of the corpus of American fictional masterpieces,and the average sentence length of 15.06 words belongs to the medium sentences category.In general,Huang’s version has the highest vocabulary richness,and Fu’s version has the lowest;in terms of vocabulary density,Huang’s has the highest and Zhang’s has the lowest;in terms of average sentence length,Fu’s has the highest,and Huang’s has the lowest.In terms of the English-Chinese word ratio,the nine versions of GWTW are higher than the average English-Chinese word ratio of 0.56,so all have over-translation of their ST.Regarding over-translation,Huang’s is the highest,and Chen’s is the lowest.The ratio of the number of idiomatic words to the total number of words in the nine versions of GWTW is the highest in Fan’s version and the lowest in Fu’s version.This feature further indicates that Fan’s are probably the closest to the conventions and norms of the Chinese language,while other translators are in descending order of closeness.Regarding positive sentiments/emotions,Fan’s version is the highest,and Fu’s version is the lowest.It was found that the text-similarity between Jia’s version and Chen’s version was the highest,followed by Fan’s translation,and then decreased with Li’s,Zhu’s,Dai’s,Fu’s,Zhang’s,and Huang’s version.2.The macroscopic quantitative affective analysis reveals that: at the level of affect categories,the ST and TT belong to “happiness”,“unhappiness”,“inclination”,“dissatisfaction” and “insecurity”;the total amount of affect in Jia’s version is the highest among the nine versions,and the closest to the total amount of affect in the ST,but there is still a gap with the ST.Fu’s version has the lowest amount of affect,which may be related to his partial deletion of the ST.The original GWTW is higher than the nine versions in terms of positive and negative emotions,with the highest amount of positive emotions in Huang’s and the lowest in Fu’s,and the highest amount of negative emotions in Jia’s and the lowest in Fu’s.As the storyline develops,the English ST and the Chinese TT show a similar pattern of affective flow,both showing a wave pattern of alternating positive and negative emotions.3.The translator can reproduce the affective connotations of the ST in the translation by employing verbs of emotional processes,adjectives,adverbs expressing qualities,nominalization of verbs and adjectives,clause and compound sentences,and text reflecting affective connotations.4.Leveraging artificial intelligence sentiment analysis technology and Appraisal Theory-based affect meaning analysis,the author cross-validated the affect meanings of the text,and the affect words of each version generally reproduce the affect meaning and characterization of the original work in terms of appearance description,utterance description,action description,psychological portrayal,and other character descriptions.The development of the plot is driven by the creation of “accidents”,the strengthening of “suspense” and the switching of the point of view.The number of translations with emotional equivalence is generally high,but there are also deviations.This is mainly due to the translators’ differences in selecting means of affective expression,affect intensity and affect types.The unfaithful translations of the versions are primarily characterized by the lack of affect meaning or the over-valuation of affect meaning in rendering,resulting in a weakening or intensification of affect intensity.5.The factors of the translator’s emotional involvement are related to the translator’s life,the translator’s habitus,and the translator’s notion.The leading translation strategies are as follows:(1)Leverage the DH approaches including the “distant reading” technique,to explore and grasp the style and affect resources of the original text,the rhythm of emotional and plot changes,and the main character’s emotional changes over time.(2)Consider the five variables of the affective connotation analysis framework from the perspective of DH in translation practice;zero translation,the addition of punctuation marks such as exclamation marks,the use of tone and modal words,the use of rhetorical patterns,and expressions that put the native language to best use are employed according to the actual context to reduce the undertranslation and overtrannslation of affective meanings caused by the differences between the English and Chinese affect representation systems.(3)Adopt affect words,affect sentences,or grammatical structures that best match or are equivalent to the affects of the original text in translation;(4)Endeavor to narrow the narrative distance and empower the narrator to narrative “on the spot”;(5)Give full play to the translation subject’s emotions: to tame their own emotions without indiscriminately applying them and convey the original’s affect without burying their emotions.The significance of this study includes:1.Incorporating the affect dimension into the study of the ST and TT of GWTW,and promoting the breadth and depth of the existing research;2.Introducing digital humanities technology represented by corpus technology,deep text mining technology,and data visualization technology into translation studies,build a fiction-based affect dictionary and a framework for analyzing the affective connotations of novels from the digital humanities perspective,to enrich the content and methods of translation studies,and realizing the mutually supportive combination of traditional qualitative affect analysis methods,AI-based sentiment analysis technology,and corpus-based affect analysis technology,the marriage of the complementary advantages and the triangulation of qualitative and quantitative analysis.By doing these,this study provides inspiration and reference for the study of affect translation in other translation styles and new strategies and methods for the affect translation of other literary works.