The language of gratitude: An empirical analysis of acknowledgments in German medical dissertations

Abstract Acknowledgment sections are a rich but underused resource for understanding how language is used for social purposes (such as expressing gratitude and communicating social relations networks), and how conventions and patterns emerge in this process. This paper presents a usage-based case study combining qualitative and quantitative methods for analyzing a dataset of >300 acknowledgment sections from medical dissertations written in German. In our quantitative analysis, we gauge keywords and key n-grams and assess the relative position of recurrent words in each text. Our analysis shows that this text type has developed clear conventions, with acknowledgments in the professional domain being followed by a usually smaller set of expressions of gratitude associated with the private domain. In addition, our quantitative analysis suggests recurrent patterns that can be linked to specific socio-pragmatic functions. For instance, an analysis of n-grams attested in text segments associated with the professional vs. the private domain shows some differences with regard to the typical patterns chosen in those segments. Our analysis also raises a number of future research questions, thus showing that acknowledgment sections are a highly interesting object of study that deserve to be investigated in more detail.

Authors

Institutions

Publication Details

Journal
Yearbook of the German Cognitive Linguistics Association
Published
2024-11-01
DOI
https://doi.org/10.1515/gcla-2024-0009
Citations
1
Primary Topic
Language, Discourse, Communication Strategies
Type
article
Field-Weighted Citation Impact
2.78
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The language of gratitude: An empirical analysis of acknowledgments in German medical dissertations

Adrian Loerbroks, Stefan Hartmann, Nils Hansson
1 citations
Yearbook of the German Cognitive Linguistics Association
Language, Discourse, Communication Strategies
2.78
article

The language of gratitude: An empirical analysis of acknowledgments in German medical dissertations

Adrian Loerbroks, Stefan Hartmann, Nils Hansson
article en
1 citations

Abstract

Abstract Acknowledgment sections are a rich but underused resource for understanding how language is used for social purposes (such as expressing gratitude and communicating social relations networks), and how conventions and patterns emerge in this process. This paper presents a usage-based case study combining qualitative and quantitative methods for analyzing a dataset of >300 acknowledgment sections from medical dissertations written in German. In our quantitative analysis, we gauge keywords and key n-grams and assess the relative position of recurrent words in each text. Our analysis shows that this text type has developed clear conventions, with acknowledgments in the professional domain being followed by a usually smaller set of expressions of gratitude associated with the private domain. In addition, our quantitative analysis suggests recurrent patterns that can be linked to specific socio-pragmatic functions. For instance, an analysis of n-grams attested in text segments associated with the professional vs. the private domain shows some differences with regard to the typical patterns chosen in those segments. Our analysis also raises a number of future research questions, thus showing that acknowledgment sections are a highly interesting object of study that deserve to be investigated in more detail.

Yearbook of the German Cognitive Linguistics AssociationVol. 12(1)
Düsseldorf University Hospital (DE), Heinrich Heine University Düsseldorf (DE)
Quality Education
Openalex Percentile: Top 9%
Language, Discourse, Communication Strategies
2.78
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.