Multi-Dimensional Exploratory Factor Analysis of TED Talks
2022, Register Studies
https://doi.org/10.1075/RS.21008.WINAbstract
This article conducts Exploratory Factor Analysis (EFA) on a corpus of TED talks (2463 talks, across 427 topic tags) to create a new Multi-Dimensional model. The resultant model contained seven dimensions: i. ‘Spontaneous involved versus edited informational discourse’, ii. ‘Abstract informational versus narrative discourse’, iii. ‘Human-world oriented versus object-oriented discourse’, iv. ‘Subjective perspectives’, v. ‘Persuasive stance’, vi. ‘Expert elaboration’, and vii. ‘Change and inspiration’. When the model was compared to prior research, similarity with MD models based in academic texts was observed. However, some dimensions were found to be indicative of the unique nature of TED talks, such as expert elaboration and change and inspiration. When the EFA model was mapped onto the TED corpus’s subcorpora (defined by topic tags), individual disciplines were characterised in terms of the dimensions and some traditional academic groups were observed.
FAQs
AI
What are the key linguistic dimensions identified in TED talks?
The exploratory factor analysis reveals seven key dimensions, such as spontaneous involved versus edited informational discourse and persuasive stance, particularly highlighted by the high loading of stance adverbials and emphatics.
How does audience interaction influence TED talk linguistic features?
TED talks often exhibit interactive features, as evidenced by the use of demonstrative pronouns and spontaneous elaboration, resulting from the preference for connecting with a general audience.
What role does academic content play in TED talks according to the study?
The study indicates that TED talks frequently feature academic content, with a substantial number of talks tagged across 21 academic disciplines, implying varied linguistic registers within this digital genre.
What methodology is used to analyze linguistic variation in the corpus?
The study employs Multi-Dimensional Exploratory Factor Analysis (MD EFA), utilizing a sample of 2,483 TED talks to quantify and group linguistic features across functional dimensions.
How do disciplinary categories influence the linguistic characteristics of TED talks?
Mapping TED talk subregisters onto identified dimensions shows that soft and hard disciplinary categories elicit distinct styles, impacting the use of narrative versus abstract discourses in presentations.
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