Multimodal Data Analysis
Quantitative Methods
Bibliographic Data
| ID | 23686292 |
|---|---|
| Authors | Yixiong Chen (0000-0002-4425-3216, Nanyang Technological University), Fei Victor Lim (0000-0003-3046-1011, Southwest University of Science and Technology) |
| Year | 2026 |
| Pages | 1-7 |
| Publication date | 2026-03-26 |
| Open Access | Yes |
| Type | CHAPTER |
| Venue | Encyclopedia of Applied Linguistics (SOURCE_BOOK) |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/9781405198431.wbeal20855 |
| OpenAlex | W7140916061 |
| ISBN | 9781405198431 |
| Language | EN |
| References cited | 7 |
Multimodality has been construed differently across various disciplines. This entry focuses on multimodality research informed by the systemic‐functional semiotic perspective (i.e., systemic‐functional semiotics). Multimodality research as such examines how meanings are made through the orchestration of multiple modes of expressions such as speech, writing, image, and gestures in contemporary communication. Systemic‐functional semiotics has witnessed the introduction and adaptation of quantitative methods from other disciplines to analyze multimodal data. To capture this methodological interdisciplinarity, the entry situates quantitative methods in current efforts to consolidate the theory‐data feedback loop in systemic‐functional semiotics and explicates how quantitative methods such as categorical methods, linear models, and data clustering techniques facilitate theoretical and methodological innovations. Specifically, this entry begins with an overview of the systemic‐functional semiotic perspective on multimodality and explains the issue of theory‐data feedback loop. The entry then discusses how aspects of multimodal meaning and meaning‐making are measured in systemic‐functional semiotic studies, and, finally, surveys key quantitative methods visible in the research literature and discusses their affordances for strengthening the theory‐data feedback loop. The entry concludes that systemic‐functional semiotics needs more studies with solid quantitative analysis to consolidate its theory‐data feedback loop while emphasizing the benefits of qualitative analysis to this end.
Affordance · Categorical variable · Gesture · Meaning (existential) · Multimodality · Orchestration · Perspective (graphical) · Semiotics
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Multimodal approach to analysing big social and news media data
Tracking visual segmentation
The potential of eye tracking data to strengthen CDA’ explanatory power
| Highly cited | No |
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