Multimodal artefacts and the texture of viewpoint

Vandelanotte, Lieven; Dancygier, Barbara

doi:10.1016/j.pragma.2017.10.011

Cited by 25 publications

(4 citation statements)

References 8 publications

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“…The understanding of viewpoint in this study builds on several broad assumptions, which I summarize here. All these aspects of perspective-taking have been discussed, in application to various discourse types, in several collections of studies (Dancygier and Sweetser, 2012;Dancygier and Vandelanotte, 2017b;Vandelanotte and Dancygier 2017).…”

Section: Introductionmentioning

confidence: 99%

Fictive Deixis, Direct Discourse, and Viewpoint Networks

Dancygier

2021

Front. Commun.

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This paper proposes a renewed and more textured understanding of the relation between deixis and direct discourse, grounded in a broader range of genres and reflecting contemporary multimodal usage. I re-consider the phenomena covered by the concept of deixis in connection to the speech situation, and, by extension, to the category of Direct Discourse, in its various functions. I propose an understanding of Direct Discourse as a construction which is a correlate of Deictic Ground. Relying on Mental Spaces Theory and the apparatus it makes available for a close analysis of viewpoint networks, I analyze examples from a range of discourse genres - textual, visual and multimodal, such as literature, political campaigns, internet memes and storefront signs. These discourse contexts use Direct Discourse Constructions but usually lack a fully profiled Deictic Ground. I propose that in such cases the Deictic Ground is not a pre-existing conceptual structure, but rather is set up ad hoc to construe non-standard uses of Direct Discourse–I refer to such construals as Fictive Deictic Grounds. In that context, I propose a re-consideration of the concept of Direct Discourse, to explain its tight correlation with the concept of deixis. I also argue for a treatment of Deictic Ground as a composite structure, which may not be fully profiled in each case, while participating in the construction of viewpoint configurations.

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Section: Introductionmentioning

confidence: 99%

Fictive Deixis, Direct Discourse, and Viewpoint Networks

Dancygier

2021

Front. Commun.

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“…Still, multimodality is analysed as a relatively restricted concept of co-verbal alignment, primarily aimed at foreground nonverbal behaviour. Nevertheless, this makes it particularly well-suited for research into co-verbal alignment within a specific function (Allwood, 2013;Arnold, 2012;Vandelanotte & Dancygier, 2017). The function of feedback and the non-verbal behaviour accompanying it, for example, was examined by Navarretta and Paggio (2020).…”

Section: Related Workmentioning

confidence: 99%

Understanding conversational interaction in multiparty conversations: the EVA Corpus

Mlakar

Verdonik

Majhenič

et al. 2022

Lang Resources & Evaluation

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This paper focuses on gaining new knowledge through observation, qualitative analytics, and cross-modal fusion of rich multi-layered conversational features expressed during multiparty discourse. The outlined research stems from the theory that speech and co-speech gestures originate from the same representation; however, the representation is not solely limited to the speech production process. Thus, the nature of how information is conveyed by synchronously fusing speech and gestures must be investigated in detail. Therefore, this paper introduces an integrated annotation scheme and methodology which opens the opportunity to study verbal (i.e., speech) and non-verbal (i.e., visual cues with a communicative intent) components independently, however, still interconnected over a common timeline. To analyse this interaction between linguistic, paralinguistic, and non-verbal components in multiparty discourse and to help improve natural language generation in embodied conversational agents, a high-quality multimodal corpus, consisting of several annotation layers spanning syntax, POS, dialogue acts, discourse markers, sentiment, emotions, non-verbal behaviour, and gesture units was built and is represented in detail. It is the first of its kind for the Slovenian language. Moreover, detailed case studies show the tendency of metadiscourse to coincide with non-verbal behaviour of non-propositional origin. The case analysis further highlights how the newly created conversational model and the corresponding information-rich consistent corpus can be exploited to deepen the understanding of multiparty discourse.

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“…These accounts prepare the ground for the development of today’s scholarship on multimodal communication analysis. The topics that scholars focus on include: multimodal research accounts of metaphor and other figurative devices [31]; critical analysis of multimodal discourse [32]; multimodal analysis of large datasets [33]; multimodal argumentation and rhetoric in media [34]; multimodal viewpoint analysis [35,36], language and gesture researched from the perspectives of cognitive linguistics [37–40], psychology of language [41–43] and semiotics [44,45].…”

Section: Introductionmentioning

confidence: 99%

Multimodal analysis of disinformation and misinformation

Wilson,

Wilkes,

Teramoto

et al. 2023

R. Soc. open sci.

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The use of disinformation and misinformation campaigns in the media has attracted much attention from academics and policy-makers. Multimodal analysis or the analysis of two or more semiotic systems—language, gestures, images, sounds, among others—in their interrelation and interaction is essential to understanding dis-/misinformation efforts because most human communication goes beyond just words. There is a confluence of many disciplines (e.g. computer science, linguistics, political science, communication studies) that are developing methods and analytical models of multimodal communication. This literature review brings research strands from these disciplines together, providing a map of the multi- and interdisciplinary landscape for multimodal analysis of dis-/misinformation. It records the substantial growth starting from the second quarter of 2020—the start of the COVID-19 epidemic in Western Europe—in the number of studies on multimodal dis-/misinformation coming from the field of computer science. The review examines that category of studies in more detail. Finally, the review identifies gaps in multimodal research on dis-/misinformation and suggests ways to bridge these gaps including future cross-disciplinary research directions. Our review provides scholars from different disciplines working on dis-/misinformation with a much needed bird's-eye view of the rapidly emerging research of multimodal dis-/misinformation.

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Multimodal artefacts and the texture of viewpoint

Cited by 25 publications

References 8 publications

Fictive Deixis, Direct Discourse, and Viewpoint Networks

Fictive Deixis, Direct Discourse, and Viewpoint Networks

Understanding conversational interaction in multiparty conversations: the EVA Corpus

Multimodal analysis of disinformation and misinformation

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