FROM LINGUISTIC FEATURES TO CULTURAL PATTERNS
PERSPECTIVES FROM LARGE-SCALE TEXT STUDIES OF DANISH SERMONS
DOI:
https://doi.org/10.7146/sss.v12i1.130067Keywords:
sermons, collective text production, large-scale text analysis, distant reading, close reading, semantic structuresAbstract
This article discusses the concept of reading and presents a method that
combines distant and close reading, while drawing on insights from
computational humanities. Focusing on basic features in language, distant
reading allows for the construction of new types of text. By close reading these
texts, it is possible to analyse cultural patterns across individual texts. This
method of reading is illustrated by two cases stemming from a project based
on a corpus of 11,955 Danish sermons. The first case begins with a distant
reading of gendered pronouns in the corpus. The second case begins with a
distant reading of named agents.*
References
Agersnap, A., R. D. Kristensen-McLachlan, K. H. Johansen, U. S. &
K. L. Nielbo (2020). Sermons as data: Introducing a corpus of
,955 Danish sermons. In: Journal of Cultural Analytics,
(2), 1-27. Online: https://doi.org/10.22148/001c.18238.
Agersnap, A. (2021). Collective testimonies to Christianity and time -
A collection and large-scale text study of 11,955 Danish
sermons from 2011-2016. (PhD dissertation). Aarhus
University, Faculty of Arts.
Agersnap, A., K. H. Johansen, & R. D. Kristensen-McLachlan (2022).
Unveiling the character gallery of sermons – A social network
analysis of 11,955 Danish sermons. In: Temenos – Nordic
Journal of Comparative Religion. [Forthcoming].
Baker, P. & T. McEnery (2015). Introduction. P. Baker and T.
McEnery (eds.) Corpora and discourse studies – Integrating
discourse and corpora, Palgrave Macmillan, 1-19.
Bastian, M., S. Heymann & M. Jacomy (2009). Gephi: An Open
Source Software for Exploring and Manipulating Networks.
In: International AAAI Conference on Weblogs and Social
Media.
Jänicke, S., G. Franzini, M. F. Cheema & G. Scheuermann (2015). On
close and distant reading in digital humanities: A survey and
future challenges. Eurographics Conference on Visualization
(EuroVis).
Evans, L. & S. Rees (2012). An interpretation of digital humanities.
D. Berry (ed.) Understanding Digital Humanities. Palgrave
MacMillan, 21-41.
Fuenmayor, D. & C. Benzmüller (2019). A computationalhermeneutic
approach for conceptual explicitation.
Á. Nepomuceno-Fernández, L. Magnani, F. J. Salguero-
Lamillar, C. Barés-Gómez & M. Fontaine (eds.) Model-based
reasoning in science and technology: Inferential models for
logic, language, cognition and computation. Springer, 441-
Lindgren, S. (2020). Data theory: Interpretive sociology and
computational methods. Cambridge: Polity Press.
Mohr, J. W., R. Wagner-Pacifici & R. L. Breiger. 2015. Toward a
computational hermeneutics. Big data & society. Online:
https://doi.org/10.1177/2053951715613809
Moretti, F. (2000). Conjectures on world literature.In: New left review,
(1), 54-68.
Moretti, F. (2007). Graphs, maps, trees – Abstract models for literary
history. London: Verso.
Nicolini, D. (2012). Practice theory, work, and organization: An
introduction. Oxford: Oxford University Press.
Piper, A. (2013). Reading’s Refrain: From Bibliography to Topology.
ELH vol. 80(2), 373-399. John Hopkins University Press.
Schnapp, J. & T. Presner (2009). Digital Humanities Manifesto 2.0.
Online:
http://www.humanitiesblast.com/manifesto/Manifesto_V2.pdf.
Tannen, D. (1992). You just don’t understand: Women and men in
conversation. London: Virago.
Wood, J. T. (2014). Gendered lives – Communication, gender and
culture. Cengage Learning.