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A Study On Image-text Relation In News Discourse From The Perspective Of Logical Function

Posted on:2024-04-13Degree:MasterType:Thesis
Country:ChinaCandidate:D Z WangFull Text:PDF
GTID:2545306935459704Subject:Foreign Linguistics and Applied Linguistics
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Multimodal researches emerged in the 1980 s and explored research frameworks for image-text relations by applying social semiotic theories to images.In 2005,Martinec and Salway applied Logical Function to study the combinations of image and text in discourse.They proposed that image and text are combined through status relations and logico-semantic relations.In this thesis,Martinec and Salway’s framework was applied to explore the features of image-text combinations in political and economic news from China Daily.The reports were initially classified based on Caple’s image-text news classification system proposed in 2013,and two types of image-text news classifications applicable to the reports collected were proposed: image-nuclear news and image-satellite news.In terms of the role of images in narrative structures of reports,the study found that in image-nuclear news,images could combine with all text constituents in a single report through logico-semantic relations and status relations.In contrast,in imagesatellite news,images only combine with captions,and it is difficult to find Logicosemantic relations and status relations between images and other text constituents such as headlines,leads,and text bodies.Based on the classification of image news,cases of realizations of status relations and logico-semantic relations between images and different textual constituents were analyzed.The study summarized several relation patterns between image and headline,image and caption,and image and other text constituents in news collected.The main findings are as follows:In the image-nuclear news,the different text constituents and images in reports exhibited varied relation patterns.(1)Headlines and images are always complementary while headlines exposit people,actions,etc.in images or enhance images by providing meanings that are hard for images to express,such as time and space.(2)Images are subordinate to captions and captions exposit,extend and enhance images.This relation pattern means that captions started from describing actions in the images and provide information that goes beyond images,such as background,time or comments on events in images.(3)In political caricatures,texts are complementary to images and the texts are projected in a speech bubble or curved line.In the image-satellite news,images are only combined with captions.Three relation patterns are found between images and captions:(1)Captions subordinate to images,which means that the captions describe the vectors in the images through material and behavioral processes without providing other information.Captions exposit and enhance images.(2)Images subordinate to captions.In this case,the processes in captions are in the past tense,with information about the past experiences of the characters in images or things that have happened.Captions extend images in this way.(3)Captions and images are independent of each other,which means that the information provided by images and captions exists as parallel.Participants in captions and images are related by componential cohesion but their processes are not related,which means that captions are adding new information for images by extension.These findings are helpful to understand the characteristics of image-text combinations in political and economic news from China Daily and provide a reference for news media to improve their image-text combinations.Furthermore,findings have proven that the application of Logical Function in analyzing the combination of images and text is effective,which may broaden the research scope of Systemic-functional Linguistics and provide some inspiration for future research on the relations between different modalities from the perspective of semantics.
Keywords/Search Tags:Logical Function, Political and Economic News in China Daily, Image-text Relation
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