What do the differences and commonalities in doctoral dissertation acknowledgments across disciplines reveal?

TL;DR

This study explores how doctoral dissertation acknowledgments differ across disciplines in Chinese universities, revealing emotional and disciplinary patterns in writing.

Contribution

The study introduces a novel approach combining BERTopic modeling and computational linguistics to analyze acknowledgments across disciplines.

Findings

Chinese doctoral acknowledgments often include emotional reflections and show distinct disciplinary traits.

Disciplines with similar characteristics have more similar acknowledgment styles and content.

Academic training influences the writing style of acknowledgments across disciplines.

Abstract

Acknowledgments in academic dissertations occupy a unique role within scholarly communication. Prior research has investigated acknowledgments through lenses such as funding attribution, genre analysis, and linguistic features. This study examines acknowledgments in doctoral dissertations from Chinese universities, organized by broad disciplinary categories. Utilizing BERTopic modeling, the research identifies topic keywords embedded within dissertation acknowledgments. Furthermore, computational linguistics techniques are employed to quantitatively evaluate the content and stylistic attributes of these acknowledgments, complemented by hierarchical clustering analysis to explore cross-disciplinary similarities. The topic modeling results indicate that acknowledgments by Chinese doctoral students frequently convey emotional reflections and exhibit distinct disciplinary traits. Additionally, hierarchical clustering shows that disciplines with similar characteristics exhibit greater similarity in the content and writing style of their acknowledgments, indicating that academic training influences researchers’ writing to some degree. This study seeks to catalyze further scholarly inquiry into this domain, advocating for expanded investigations from perspectives including psychology, neuroscience, and cross-cultural studies.

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