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Examining Motivating Language in Commencement Speeches Using Epistemic Network Analysis

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Advances in Quantitative Ethnography (ICQE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1895))

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Abstract

This research examines how speakers use language to motivate their audiences through an analysis of 15 Harvard University commencement speeches from 2007 to 2021. Motivating language theory classifies the data and interprets the result as a theoretical framework. This study modeled the language patterns employed by the speakers using Epistemic Network Analysis (ENA) and compared the ENA network model based on gender and time. Results indicate that meaning-making language serves as a dominant approach to motivating audiences. Particularly, the speakers mainly employed personal anecdotes or enlightenment, knowledge related to their own experience, and suggestion language to imply specific actions or ideas. Additionally, the differences in motivational language patterns between male and female speakers and between older and more recent speeches were found. These findings could help organizational leaders, who must communicate or speak to employees, motivate them to commit and engage with their work.

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Author information

Authors and Affiliations

  1. Ministry of Culture, Sports, and Tourism in Korean Government, Sejong, 30119, Republic of Korea

    Yujung Seol

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  1. Yujung Seol
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Correspondence to Yujung Seol .

Editor information

Editors and Affiliations

  1. Clemson University, Clemson, SC, USA

    Golnaz Arastoopour Irgens

  2. University of Technology Sydney, Ultimo, NSW, Australia

    Simon Knight

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Seol, Y. (2023). Examining Motivating Language in Commencement Speeches Using Epistemic Network Analysis. In: Arastoopour Irgens, G., Knight, S. (eds) Advances in Quantitative Ethnography. ICQE 2023. Communications in Computer and Information Science, vol 1895. Springer, Cham. https://doi.org/10.1007/978-3-031-47014-1_12

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  • DOI: https://doi.org/10.1007/978-3-031-47014-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47013-4

  • Online ISBN: 978-3-031-47014-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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