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## FROM LINGUISTIC FEATURES TO CULTURAL PATTERNS: PERSPECTIVES FROM LARGE-SCALE TEXT STUDIES OF DANISH SERMONS

Anne Agersnap Aarhus University anag@cas.au.dk

Kirstine Helboe Johansen Aarhus University kp@cas.au.dk

## Abstract

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. *

Keywords: Sermons, collective text productions, large-scale text analysis, distant reading, close reading, semantic structures

## 1. Introduction

A sermon is an oral event. People gathered for Sunday service sit in the pews listening to the preacher's words. In a Danish context, a sermon is typically also a written manuscript and a text file on the preacher's computer. The preacher may revise the manuscript several times, reuse it or come back to it later for inspiration. It might also be published on the church website or in a booklet. Like any other speech, a sermon is the  words  of  the  orator  at  the  spoken  event  and  in  the  written manuscript. However, a sermon is also a genre and a shared practice. As a genre, it is bound to its setting and occasion, and it is an established practice for which pastors are trained, leaning on the long tradition of preaching preceding them. Whereas preaching as an oral event is bound to the moment in which it takes place, sermon manuscripts manifest the sermons as concrete objects and enable them to be archived as resources for  later.  As  objects,  sermon  manuscripts  document  preaching  as ongoing cultural productions - as a collective  practice  of  preaching. Literary scholar Franco Moretti famously brought attention to text in terms of quantity, which allows text productions to be understood as collective  systems  (Moretti  2007:3-4).  We  argue  that  also  sermons should be studied as a collective system. To study texts as collective systems entails  new understandings of what reading is and demands distinct  methodological  tools  to  interpret  the  cultural  significance  of these practices. However, before we can extract cultural information from them, we need to step back and think of texts as 'language'.

* We owe special thanks for the engaging comments following the review of our article. Moreover, we are grateful for our engaging and fruitful partnership with Ross Deans Kristensen-McLachlan, Uffe Schjødt and Kristoffer Laigaard Nielbo. The case studies we present in this article have been conducted in collaboration with all project partners in the sermon project.

In  an  ongoing  collaborative  sermon  project  investigating  a corpus of 11,955 Danish sermons, we have strived to study sermons from this perspective with the overall objective to uncover how pastors in their sermons navigate between religious tradition and contemporary culture. Neither of us are trained linguists. Nevertheless, to achieve our goal of approaching sermons as a collective practice, we have explored new ways of reading our material, and the strategy that proved most insightful  was  to  focus  on  basic  linguistic  features.  In  our  case,  this means paying attention to words and texts based on linguistic coherence structures,  such  as  syntactic  function  of  terms  as  well  as  relations between  certain  parts  of  speech  in  language.  Thus,  underlying  the overall  objective  of  the  sermon  project  was  an  implicit  and  more methodological question: How can we through basic linguistic features access culturally significant information in large text collections?

In this article, we demonstrate how this underlying question has guided the sermon project and allowed us to gain culturally significant information, thereby helping us to achieve the overall objective. The two case studies presented in the following show how we by attending to  basic  features  such  as  gendered  pronouns and  named  agents have gained  insight  into  gender  and  religion  and  into  relations  between cultural and religious domains.

## 2. The sermon project: A collection and large-scale text study of 11,955 Danish sermons

The sermon project is a collaborative project with expertise from 'the sociology of religion' , 'practical theology' and 'computational humanities'. 1 The cases included in this article were initiated within the framework of Anne Agersnap's PhD project (Agersnap 2021). As part of  the  PhD  project,  Agersnap  assembled  a  text  corpus  of  11,955 sermons including basic socio-demographic variables from 95 pastors in the Evangelical-Lutheran Church in Denmark (ELCD). All sermons were received directly from the pastors via e-mail and carefully cleaned, annotated and archived as a digital corpus (Agersnap et al. 2020). Due to the size and quality of this new data set, the corpus offers previously inaccessible  knowledge  about  how  pastors  in  the  ELCD  practice religion and culture.

The  sermon  project  aims  to  study  sermons  as  a  collective production  of  texts  conceived  in  the  intersection  of  tradition  and contemporary culture. The main research question is: how do pastors' collective  encounters  with  Christianity  and  cultural  fields  unfold  in sermons? Sunday after Sunday, year after year, pastors in the ELCD are obliged to expound prescribed and recurring biblical passages in their sermons  as  part  of  church  services.  While  the  biblical  texts  are prescribed by a cyclical church calendar, the momentary situation in which the biblical passages are interpreted is always new. Sermons are therefore  deeply  intertextual  and  entail  a  unique  meeting  between biblical and contemporary time (Agersnap 2021).

The ELCD employs roughly 2,000 pastors, and most pastors write down their sermons as a manuscript prior to the church service. This means that pastors collectively and continuously contribute to a comprehensive production of texts- even though the sermons remain the property of the individual pastors after the service. With the newly established sermon corpus, we have studied how pastors collectively navigate  between  Christian  tradition  and  contemporary  culture.  The case studies included in this article were originally designed to address this  overall  question.  The  first  study  explores  the  role  of  cultural discourses in sermons with a focus on gender constructions, while the second  study  investigates  how  cultural  and  biblical  domains  are encountered in sermons. The main purpose of the cases in this article is, however, not to provide sociological and theological answers, but to demonstrate and discuss how automated linguistic tools have enabled us to pursue these questions.

1 The sermon project is based at Aarhus University, and the project partners include associate professor in practical theology Kirstine Helboe Johansen, PhD in the study of religion Anne Agersnap, associate professor in the study of religion Uffe Schjødt, software engineer at the Centre for Computational Humanities Aarhus Ross Deans Kristensen-McLachlan and associate professor and leader of the Centre for Computational Humanities Aarhus Kristoffer Laigaard Nielbo.

## 3. What is reading and what do we read?

The magnitude of 11,955 sermons naturally complicates an initial indepth reading of the material before commencing analysis. Thus, upon archiving the sermons, we had not read any of the manuscripts in full, meaning that we did not know the content of the individual sermons. While we have no prior knowledge of the specific subject matter in the sermons, we can presume that all pastors rely on fundamental linguistic principles in order to construct coherent texts. All of the included case studies  are  therefore  based  on  a  fundamental  understanding  of  the corpus  as  a  collection  of  language.  However,  uncovering  linguistic structures is not our immediate purpose. Rather, our aim is to identify semantic  patterns  as  collective  representations  in  the  text  collection through information carried by linguistic features. Therefore, we need to develop pipelines that allow us to uncover cultural information in the form of semantic structures from naturally occurring linguistic features in the text collection. This includes methods to automatically juxtapose and  contrast  content  in  each  document  with  content  in  all  other documents in the corpus. These pipelines include a process of 'distant reading' and 'close reading'.

## 3.1 Distant reading

The concept of 'distant reading' is associated with the works of Franco Moretti  (Moretti  2000),  and  has  since  then  been  a  common  concept within the 'digital humanities'. Moretti used the term to explicate what it means to study texts through the aid of computational resources, when working  with  large  literary  corpora.  This  approach  entails  applying computational  and  quantitative  visualisation  techniques  to  represent large collections of texts in different ways - for example in the form of graphs,  maps  or  trees  (ibid.  2007).  In  a  state-of-the-art  report  on common digital visualisation techniques, Stefan Jänicke and collegues (2015) review concrete tools and techniques used to perform distant reading by summarising large data sets - such as heat maps, geospatial maps and a range of graph visualisation tools.

We use the concept of distant reading in a slightly different way than Moretti and Jänicke and colleagues (2015), as distant reading in our methodology defines the initial phase of the analytical process. This phase includes targeting relevant linguistic components and quantifying the relationship between them, which requires computational resources. In each  of the case studies -whether  they  investigate  gender constructions  or  cultural  and  religious  domains  -  we  need  to  be extremely clear as to how we observe those phenomena in the corpus. Furthermore, since we study sermons as a collective production of texts, we need to target text phenomena that can potentially occur in each of the  texts  in  the  corpus.  Our  overall  approach  is  therefore  to  target generic  linguistic  text  components  that,  in  relation  to  other  text components,  implicitly  carry  information  about  pastors'  handling  of cultural  and  religious  discourses.  In  both  case  studies,  we  apply automated tools developed based on linguistic principles that can target and retrieve specific text components individually or in relation to other components. With this strategy, our distant reading dissolves the natural coherence and structure of the corpus texts, as we remove specific text features from their original text context. What we are left with is a text structure that runs across the text collection and thus reveals a pattern of repetitive relations. The distant reading, however, leaves us with no interpretation  of  this  pattern.  Instead,  it  provides  us  with  a  new  and reconstructed text that requires a 'close reading'. Thus, in our use of the concept, distant reading is a method that implies creating new types of texts for close reading. It is rarely a full reading in itself.

## 3.2 Close reading

Moretti originally used the term distant reading to challenge traditional text readings and perspectives within literary scholarship that required meticulous scrutiny of literary works individually. He argued that such close readings cannot target the vast majority of works from a given period,  and scholars therefore tend to overlook 'the great unread' of literature  (Moretti  2000).  Consequently,  the  same  'few'  works  are studied over and over again, which leaves behind canonised understandings of literary epochs (ibid. 2007). Jänicke and colleagues (2015) demonstrate that close reading does not necessarily contrast with digitally informed text studies, as they present various tools used for visualising  and  annotating  individual  texts  (i.e.  not  large-scale  text collections) in creative and helpful ways.

In our methodology, close reading is not the practice of full text reading as problematised by Moretti, nor is it the process of computationally  re-visualising  individual  texts  as  demonstrated  by Jänicke  and  colleagues.  Instead,  we  use  the  term  to  define  the interpretative  phase  of  the  analytical  process,  which  entails  closely reading and understanding the cultural and religious significance of the recomposed text that we retrieve computationally through our distant reading. This close reading requires no computational competency in itself, but implicates a traditional meeting between text and analyst even though the text looks different from the form and structure that humanist scholars traditionally work with. When we insist that close reading is an inherent part of the analytical process of large-scale text studies,  we  emphasise  that  in  the  end,  we  are  first  and  foremost interested  in  our  study  object  as  texts  rather  than  as  numbers.  The automated analyses and quantitative measurements are not the goal, but the means to perform close readings of text phenomena in large-scale text  collections.  Therefore,  the  aim  of  the  close  readings  in  the  case studies is to analyse and interpret the structures that have emerged from distant readings in order to understand what these patterns established tell us about sermons. Just like with distant reading, we consider close reading  a  generic  analytical  phase,  and  the  concrete  undertaking  of close reading therefore depends on specific questions and design. In the specific cases that follow, the close readings entail top-down as well as bottom-up  coding  analysis  known  from  text  studies  in  the  social sciences. In the same way as a range of different computational tools can be deployed for distant reading depending on the concrete questions and  data,  we  believe  that  close  reading  as  defined  above  can,  in principle, be carried out through adaptations of text analysis from other and different humanist disciplines.

Overall,  our  use  of  distant  and  close  reading  implies  a  shift between  first  distancing  ourselves  from  the  individual  sermons  and observing patterns across the text collection, and then zooming in on these patterns to observe and interpret them closely. The distant reading analysis  makes  it  possible  to  observe  semantic  structures  in  the sermons, while the close reading analysis makes it possible to interpret and  contextualise  the  semantic  content.  Thus,  our  approach  is  a movement between complexity reductions (removing text abundance to get a clear view of the targeted text features) and complexity increases (interpreting the various dynamics that allow these patterns to emerge in sermons). 2

2 The methodology of distant and close reading was initially developed in Agersnap's PhD dissertation (see Agersnap 2021).

## 4. Case studies: Distant and close readings of cultural and religious patterns

Both  of  the  case  studies  are  motivated  and  framed  within  different disciplines - 'practical theology', 'the sociology of religion' and 'the digital  humanities'  -  and  consequently  presented  in  publications  for different audiences. In the following, our primary venture with the cases is  methodological,  as  we  present  the  application  of  automated  and linguistically  based  tools  and  the  shift  between  distant  and  close reading. The background, research context and findings of each case will therefore only be stated briefly.

## 4.1 Gender discourse in sermons

Unlike  other church  traditions today, gender  theologies are not explicitly prominent in the Evangelical-Lutheran Church of Denmark. Meanwhile, discussions of gender equality have become increasingly conspicuous  in  Danish  society  over  the  last  years.  We  therefore designed  this study to explore implicitly how  pastors  represent gendered characters  in  their  sermons  in  the  contemporary  discursive climate in society 3 .

Our entry point is  male and female personal pronouns in the nominative  case  (Danish han 'he'  and hun 'she')  and  oblique  cases (Danish ham 'him'  and hende 'her')  and  their  associated  verbs. Gendered pronouns provide concrete text features that are thoroughly integrated in the Danish language to point out characters as gendered. With  their  associated  verbs,  we  are  able  to  observe  on  a  very fundamental level the agency patterns that pastors ascribe to female and male  agents,  respectively.  Before  retrieving  text  components,  we segment  the  full  sermon  corpus  into  two  separate  sub-corpora,  one including sermons from female pastors and one from male pastors. This allows  us  to  study  gender  on  two  levels:  how  gender  'in'  texts  is constructed,  and  whether  text  constructions  differ  depending  on  the gender  of  the  authors  'behind'  the  texts.  As  we  design  the  study  to include  gender  categories  thoroughly  integrated  in  Danish  language use, we are not able to consider more diverse understandings of gender in this study.  Alternative  designations  of  gender  would  not  be particularly widespread - if at all - in the corpus. With our approach, we are able to observe gender categories in the full collection.

As a first step in our distant reading pipeline, we use a part-ofspeech tagger (POS tagger) that automatically recognises and annotates word classes in texts. From the annotated corpora, we retrieve every instance  of  one  of  the  four  types  of  gendered  pronouns  and  their associated verbs. This gives us a list of 3,314 unique verbs in sermons by women and 3,765 unique verbs in sermons by men. We then measure the relationship between each verb and each of the four pronouns by calculating 'pointwise mutual information' scores (PMI scores). PMI scores measure how strongly a verb is associated with each pronoun in comparison to the remaining pronouns. If the score is above 0, there is a significant and systematic pronoun-verb relationship; if the score is below 0, there is a systematic non-relationship between pronoun and verb; and if the score is 0, there is no systematic relationship, meaning that it is arbitrary whether verb and pronoun co-occur. This measuring system  devalues  verbs  that  occur  frequently  and  are  commonly associated with all four pronouns - such as the Danish siger 'says', er 'is' and kommer 'comes'. Therefore, verbs that do not indicate gender dependency are automatically discarded. However, this also means that verbs that are used rarely in the corpora are more likely to obtain high PMI  scores.  To  avoid  these  outliers,  we  discard  verbs  that  have  a frequency  score  below  10  in  sermons  by  male  and  female  pastors, respectively.

3 The full study appears in Agersnap and colleagues (2020).

This  distant  reading  pipeline  -  annotating,  retrieving  and measuring data - outputs a table for each sub-corpora with the verbs as rows, pronouns as columns and PMI scores as the cells designating the associative  strength  of  the  relationship  between  pronouns  and  verbs. With these steps, we have recomposed the corpora into a new form of text. Figure 1 is an illustration of the content and structure of this text type.

18

16

afbilledet

38

0.9516151458451036

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14

afbilde

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15

13

advaret

23

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14

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advarer

80

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3.1275254794483494

13

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advarede

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adskilte

24

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adskilt

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adskille

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0.0

4.870494784506972

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adresseret

0.0

5.768557865482679

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adlyder

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3.5172660668761835

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adlyde

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accepteret

63

accepterer

64

32

200

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|   0.4460665791799567 | 1.123465402771763   |   2.4789881052249 | 0.0                | han   |
|----------------------|---------------------|-------------------|--------------------|-------|
|                  0.0 | 0.0                 |               0.0 | 0.0                | ham   |
|                  0.0 | 4.223102332944/38   |               0.0 | 1.0042265080/633/1 | hun   |

frequency The data used for close readings is based on these new tabular texts (one from  each  sub-corpora).  It  provides  an  overview  of  the  verbs  most strongly associated with the pronouns individually, which allow us to define and interpret the agency pattern for the male and female subjects ( han and hun ). However, we also sort the table to show the verbs most related  to  a  pronoun  in  the  nominative  case  (such  as hun )  and  to  a pronoun of opposite gender in the  oblique  case  (such  as ham ).  This means that we can detect the type of action most likely to be performed by a female agent towards a male agent and vice versa. We thus study four types of agency patterns in each sub-corpora - one pattern for male subjects, one for female subjects and two for interacting agents ( he-her and she-him ). We use a qualitative coding strategy to categorise agency types bottom-up by closely reading and evaluating the verbs assigned to the agent classes. This strategy discloses four agency categories that were dispersed differently in the agent classes and in the sub-corpora: 'active-competent agency' (verbs that express acts of vigour); 'cogitative-perceptive agency' (verbs that express acts of sensing and interpreting); 'communicative-expressive agency' (verbs that express extroverted or contact-oriented acts); and 'religious agency' (verbs that express acts connected to a religious context in particular). See table 1 for  an  example  of  the  categories  represented  for  male  and  female subjects individually ( han and hun ) in sermons by female pastors.

Figure 1: Excerpt of PMI data for close reading

|                                  | Single case: Male subject   | Single case: Male subject   | Single case: Male subject   | Single case: Female subject   | Single case: Female subject   | Single case: Female subject   |
|----------------------------------|-----------------------------|-----------------------------|-----------------------------|-------------------------------|-------------------------------|-------------------------------|
| Category                         | Verb                        | Freq.                       | PMI                         | Verb                          | Freq.                         | PMI                           |
| Active- Competent agency         | Undertook                   | 21                          | 3.2                         | Gave birth                    | 72                            | 5.2                           |
| Active- Competent agency         | Promise                     | 388                         | 2.9                         | Involves                      | 20                            | 4.0                           |
| Active- Competent agency         | Overcame                    | 57                          | 29                          | Managed                       | 37                            | 3.4                           |
| Active- Competent agency         | Direct                      | 82                          | 2.8                         | Achieve                       | 39                            | 3.3                           |
| Cogitative- Perceptive agency    | Sensed                      | 29                          | 3.0                         | Misunderstan d                | 28                            | 4.1                           |
| Cogitative- Perceptive agency    | Regrets                     | 63                          | 2.8                         | Dreamt                        | 82                            | 3.7                           |
| Cogitative- Perceptive agency    | Decides                     | 87                          | 2.9                         | Imagined                      | 42                            | 3.6                           |
| Cogitative- Perceptive agency    | %                           | %                           | %                           | Recognises                    | 201                           | 3.3                           |
| Communicative -Expressive agency | Discussed                   | 32                          | 3.1                         | Greeted                       | 22                            | 4.3                           |
| Communicative -Expressive agency | Propagate                   | 32                          | 2.9                         | Kisses                        | 72                            | 4.3                           |
| Communicative -Expressive agency | Declare                     | 32                          | 3.1                         | Cries                         | 366                           | 3.4                           |
| Communicative -Expressive agency | Asserted                    | 27                          | 3.2                         | Expressed                     | 83                            | 3.3                           |

Sermonised

129

2.8

Anointed

110

3.2

Table 1: Distribution of analytical categories in sermons by female pastors. The table presents verbs representative of one of the four categories.

| Religious agency   | Heals    |   213 |   2.8 | %   | %   | %   |
|--------------------|----------|-------|-------|-----|-----|-----|
| Religious agency   | Preached |   101 |   2.8 | %   | %   | %   |
| Religious agency   | Revealed |   101 |   2.8 | %   | %   | %   |

The analyses show that male and female pastors ascribe the categories differently to female and male agents. Male pastors seem to reserve the 'active-competent agency' to male subjects and 'cogitative-perceptive agency'  and  'communicative-expressive  agency'  to  female  subjects. Comparatively,  female  pastors  distribute  these  three  agency  traits  to male and female agents alike. 'Religious agency' is a trait mostly found in sermons by women, who in particular ascribe it to male subjects or to female subjects ( hun ) interacting with a male object ( ham ).

These findings suggest that male pastors represent social worlds with a clear difference between the agential spaces of male and female characters, while female pastors represent social worlds indicating that female and male characters hold more and similar agential spaces. Our interpretation  of  these  observations  is  that  pastors  reassert  general social patterns pertaining to men and women. In sociolinguistic theory (Wood 2014:102-122, Tannen 1992:23-95), male speech communities are  characterised  by  language  used  to  assert  differences  between conversational  partners  and  language  used  instrumentally  to  provide solutions for concrete objectives. Comparatively, female speech communities  are  characterised  by  a  language  that  seeks  to  establish connections  between  communicating  partners  and  language  used  to display support and responsiveness. Male speech communities are thus concerned with asymmetric relationships and female speech communities with symmetric relationships. The findings thus suggest that sermons are not gender-neutral documents, but influenced by the socialisation processes that tend to pertain to men and women. From these  observations,  we  cannot  say  whether  these  traits  affect  the theologies  that  male  and  female  pastors  represent.  Instead,  we  can observe  that  discursive  strategies  in  society  at  large  also  exist  in sermons and that the social worlds in sermons are affected by the social reality that pastors themselves are part of.

## 4.2 Cultural and religious domains in sermons

The purpose of the second case study is to explore which aspects of culture  and  Christian  tradition  pastors  tend  to  interact  with  most distinctly  in  sermons.  Similar  to  the  first  case  study,  we  want  to investigate  these  tendencies  based  on  features  that  are  common  in language and therefore bound to be widely disseminated in sermons. Following this principle, we choose named characters as features for the  study,  since  language  tends  to  revolve  around  subjects  doing something.  In  contrast  to  for  example  literature,  sermons  are  not fictional  texts,  and  pastors  therefore  do  not  construct  characters  in sermons freely.  Instead,  pastors  invite  characters  in  from  a  range  of different contexts, whether biblical, literary, political, popular cultural, contemporary  or  historical.  The  characters  in  sermons  consequently provide unique insight into the aspects of culture and Christian tradition that  pastors  represent  the  most  and  most  distinctly 4 .  We  develop  a pipeline to extract and label characters from the sermon corpus and to study character relationships in order to disclose how characters and thereby cultural and religious domains interact in sermons. The pipeline includes more than one shift between distant and close reading.

In the first phase of distant reading, we use a tool for 'namedentity  recognition'  (NER)  to  automatically  detect  and  retrieve  all characters in the corpus. The NER tagger is trained to identify entities such as persons, locations and organisations based on their syntactical position and  function in the texts. We  only  include  characters mentioned  10  times  or  more  in  the  corpus,  and  based  on  this information, we then obtain a tabular overview of the most frequent characters in the corpus. In the first phase of close reading, we label each character in order to categorise them. First, we distinguish between four  main  types:  biblical  characters  ( Jesus,  God ),  non-biblical  but known  characters  ( Astrid  Lindgren,  Hitler ),  non-specific  characters holding a proper noun ( Anders,  Sophie ) and characters  named according to a role or function (Danish kongen 'the king' ,  gartneren 'the gardener'). For the purpose of the study, we are most interested in the biblical characters, which we sub-label as New Testament or Old Testament characters, and the non-biblical characters, which we sublabel according to the cultural domain they represent - such as literary authors or politicians. All characters are sub-labelled in regard to gender and geographical origin as far as possible. See the coding manual below in table 2.

4 The full study appears in Agersnap and colleagues (2022).

| CATEGORY    | CODE   | DEFINITION                                                          |
|-------------|--------|---------------------------------------------------------------------|
| Type        | B      | Biblical character                                                  |
|             | B_a    | Ambiguous biblical character                                        |
|             | N      | Non-biblical character                                              |
|             | P      | Proper nouns                                                        |
|             | R      | Social role                                                         |
| Gender      | 1      | Male character                                                      |
|             | 2      | Female character                                                    |
|             | 0      | Character unidentifiable as male or female                          |
| Time        | OT     | Old testament character                                             |
|             | NT     | New testament character                                             |
|             | ONT    | Character or name in the old and new testament                      |
|             | CON    | Character who was alive in 2011-2016                                |
|             | PAST   | Character who was not alive from 2011-2016                          |
| Nationality | DK     | Danish character Icelandic, Finnish, Swedish, Norwegian, Faroese or |
|             | NOR    | Greenlandic character                                               |
|             | EUR    | European character                                                  |
|             | NAM    | US or Canadian character                                            |
|             | GLO    | Non-European and non-North American character                       |
| Domain      | POL    | Politician                                                          |
|             | LIT    | Fictional writer                                                    |
|             | MUS    | Musician                                                            |
|             | ART    | Artist within the visual arts                                       |
|             | THE    | Theologian                                                          |
|             | ACT    | Actor                                                               |
|             | ROY    | Royal character                                                     |
|             | REA    | Character from reality show                                         |
|             | TV     | TV personality (show host, anchor etc.)                             |
|             | RAD    | Radio personality (show host, anchor etc.)                          |
|             | SOC    | Social media personality (bloggers, youtubers etc.)                 |
|             | SPO    | Athlete                                                             |
|             | BUS    | Personality associated with business communities                    |
|             | ACA    | Academic                                                            |

DEB

Public voices or debaters

FIC

Fictional character ex. from literature, movies, tv

shows etc.

LEG

Legendary character

OUT

Unidentifiable character

Table 2: Coding manual for named entities

This  process  demonstrates  that  our  use  of  close  reading  does  not necessarily equate to a qualitative reading, since the labelling procedure provides our data with quantitative variables. Most importantly, close reading in our terminology entails observing and evaluating retrieved data meticulously through a process that presupposes automated text processing, but cannot be automated itself. With this first phase of close reading,  we  therefore  manage  to  correct  some  of  the  flaws  and insufficiencies made by the NER tagger - such as different spellings of the  same  character  or  text  components  wrongly  tagged  as  personal entities. By correcting these mistakes, we end up with a data set of 600 unique characters. We thus use the first analytical phase of close and distant  reading  to  get  an  overview  of  the  frequencies  and  types  of characters in the corpus.

In the second analytical phase, we perform a 'social network analysis'  (SNA)  to  investigate  how  these  characters  encounter  each other in sermons. SNA measures and describes how components in any type of system, called 'nodes', interact or relate to each other, which is visually demonstrated by an 'edge' between nodes. As a tool for distant reading,  we  use  the  open-access  program  Gephi  to  construct  and statistically evaluate the character network (Bastian et al. 2009). In our network,  the  retrieved  characters  are  the  nodes,  and  the  edges  -  the relationship between characters - are defined as the co-occurrence of characters in a sermon. We use Gephi to detect sub-groups of characters in the full network with the program's community detection algorithm. The  algorithm  detects  10  modularity  classes  (i.e.  sub-groups)  of characters  that  tend  to  co-occur  systematically  or  to  co-occur  with similar characters. This procedure provides us with a rematerialised text in tabular form with characters as rows and all network parameters including  modularity  classes  -  and  previously  assigned  labels  as columns. See figure 2 below.

27 | Kai Munk

26 Elias

1 OT

THE

164

376

4. 0.5182

4 0,5124

0.5569

0,553979

338714385

0.08224

236421947 0,08743

0.08224 0.003581

0,08743 0,003561

0.42315|

1371

0.40209

172 N

1 THE PAST DK

0,48359

1606

0,424939

448 B\_a

1 OT OT

25 Jeremias

1 B

1 OT

84

0,52

23 Menneskesøn/Mennes

1 B

1 ONT

86

385

24 Satan

1 B

0 ONT

86

314

4 0,5159

0,559683

0,52

0,560796

0,558292

439219629

284620052

0,08359

605684681

0,08743

0,08359

0,08743

0,00376

0,40333

1406

0,40952

280 B

1 OT OT

0,00374

0,43529

1591

0,426479

279 B

O ONT ONT %

0,08915

0,08915 0,003842

0,44679

1633

0,434789

258 B

1 ONT ONT

22|

Pontius Pilatus

1 B

1 NT

94

338

4 0,5231

3 0,5273

0,570117

0,567195

31800628

6261076

0,09769

0,09769

0,00405

0,45733

1999

0,475873

267 B

1 NT

NT

0,09025

0,09025 0,004276

0,3794

1694

0,441784

177 B

1 NT

21 Augustus/Kejser Augu:

1 B

1 NT

20 Faderen/Fader

1 B\_a

1 NI

109

568

19 Herodes

1 B

1 NT

120

721

4 0,5348

4 0,5401

0,591681

0,582499

1344412206

David/Kong David

B a

1 OT

122

885

4 0,5411

0,59335

17| Gud

1 B

0 ONT

126

651

4 0,5445

0,597524

957880752

1093652657

0,10844

0,10261

0,10261 0,004959

0,36731

2162

0,501743

429 B\_a

1 NT

132921153

0,1099

0,11214

0,108440,005276

0,1099 0,005368

0,11214 0,005607

0,33978

2426

0,530484

847 B

1 NT

0,32343

0,33261

2455

0,538623

1060 B\_a

1 OT OT

2547

0,549375

357 B

0 ONT ONT %

16 Esajas

1 0T

133

1119

15 Søren Kierkegaard

1 THE

158

541

4 0,5485

4 0,5598

0,623678

0,603645

111787464

2678520567

0,1173

0,12372

0,12372 0,007131

0,1173 0,005818

0,31397

0,24752

2756

0,575045

989 B

1 01 01

3070

0,609682

614 N

1 THE PAST DK

14 N.F.S. Grundtvig

1 N

1 THE

206

1081

13 Martin Luther

1 N

1 THE

214

1228

0,599

4 0,5925

0,674318

0,666806

5506629742

6293308131

0,14735

0,14863

0,14735

0,009974

0,14863 0,009568

0,20549

4339

0,735544

1154 N

1 THE PAST DK

0,18446

4204

0,73138

1481 N

1 THE PAST EUR

12 Herren

1 B\_a

1 ONT

293

10 Stéphane Hessel

ON

11 Adriana

0 P

2 %

1 DEB

M M

1492

3 0,6561

2509

4 0,4291

0,742348

4 0,4291

0,44616

14410367563

4 0,5445

0,600306

0,44616

2629781649

0,00265

8 Maria

0 B\_a

2 NI

81

7 Johannes

0 B a

1 NT

149

3823

2765

4 0,5195

4 0,5567

0,557735

0,617001

270015152

0,10851

0,00265

0,17404

0,002650,000294

0,17403 0,013926

0,13486

5769

0,871372

1249 B\_a

1 ONT ONT %

0,00265 0,000294

201945223

0,08777

0,10851 0,00615

0,27704

2359

0,533491

6066 B\_a

1 NT NT

0,12013

0,12013 0,006668

0,087770,003542

0,48827

1582

0,427601

6003 B\_a

2 NT NI

0,26102

2878

0,591119

6398 B a

1 NT NT

0,013887

12 P

2 % %

0,013887

18 N

1 DEB CON EUR

9 Peter/Simon Peter

0 B a

1 NT

6 Jakob

o B\_a

1 ONT

116

1177

Paulus/Saulus

0 B

1 NT

182

3486

4 0,5392

4 0,5776

0,646216

0,588898

121081952

2850001301

0,1026

0,13998

0,13998 0,008123

0,1026 0,005204

0,31934|

0,23381

2130

0,503115

1669 B\_a

1 ONT ONT %

3851

0,689483

3802 B

1 NT NT

Josef

0 B

1 ONT

101

1391

4 0,5292

0,574708

110/08/581

0,09464

0,09464 0,004537

0,36436

1840

0,463246

1754 B

1 ONT ONT

Kristus

1 NI

204

2892

4 0,5907

0,664858

4408255909

0,14445

0,14445 0,009247

0,19477

4033

0,714983

2384 B

1 NT NT

Jesus/Jesus Kristus

0 B

1 NI

405

9859

3 0,7506

0,836672

39839452724 0,19717 0,19717 0,021025

0,08844

7235

89228 B

1 NT NT

1 Id

\_modulai Domain Gender Type Degree Weighted Eccen closness harmonicclo betweenesscent Authority Hub

pageranks clustering triangles eigencentrality Frequenc Type | Gender Doma Time Nationa We use the table for a close reading of the modularity classes, focusing on  the  thematic  contexts  that  the  characters,  based  on  their  original domain, represent now through their connections to other characters. The first phase of close reading thus identifies the broader cultural or religious  context  that  sermon  characters  represent,  while  the  second phase of close reading considers the context which the characters enter into 'in' sermons.

Figure 2: Excerpt from network data including statistical parameters and manually assigned labels

<!-- image -->

The  network  analysis  unveils  three  interesting  types  of  subgroupings.  Most  of  the  sub-groupings  constitute  narrative  clusters highlighting different stories and roles of Jesus: 'the saviour', based on connections with New and Old Testament characters representative of the nativity narrative in the bible; 'the teacher', based on connections with  New  Testament  characters  from  gospel  texts  associated  to  the Trinity season of the church calendar 5 ; and 'the compassionate', based on connections with  biblical outcasts, but also literary authors, writing about moral and the breaking of norms ( Fyodor Dostoyevsky, Astrid Lindgren) .

Another type of sub-group represents a theme connected to thisworldly strife and evil. The most central figure in the cluster is Adolf Hitler, who, along with other political figures, comprises a World War II motif. Furthermore, the sub-group includes a group of terrorists, such as  the  Norwegian  perpetrator  Anders  Breivik.  This  sub-group  of historical and contemporary figures constitutes a problematic domain in the sermons revolving around this-worldly atrocities and evil.

The  final and largest sub-group  in the network  data is characterised by containing characters with low frequency scores who do not co-occur with many other characters in the corpus. This means that what links them as a group is that they are all anonymous characters in  the  sermons,  unable  to  connect  to  coherent  narratives,  whether biblical  or  historical.  These  figures  are  in  particular  contemporary figures and Old Testament characters.

The  sub-groups  demonstrate  which  narratives and motifs pastors in the corpus agree the most about disseminating. Our findings show that pastors agree about enhancing some gospel narratives rather than others. For every church service in the church calendar, pastors in the ELCD are obliged to read aloud a prescribed gospel passage before giving their sermon, and they are supposed to base their sermon on this passage.  Since  the  nativity  narrative  and  trinity  stories  appear  as coherent structures in the network data, we hypothesise that pastors at large  paraphrase  and  deal  with  these  narratives  in  particular  as compared to other gospel passages in the church year. Meanwhile, in sermons about biblical outcasts, pastors tend to include characters from a  literary  domain  as  well  to  emphasise  certain  themes  of  the  gospel passages. In comparison to the biblical clusters, the cluster centred on a World War II motif and worldly atrocities illustrates a consensus among pastors  that  this  particular  historical  period  is  important  in  a  church context. In contrast, the large group of anonymous figures is made up of the characters whose roles and relevance pastors are not in agreement about  yet,  but  may  be  negotiating.  We  hypothesise  that  these  'new' figures  over  time  may  obtain  a  more  central  status  or  disappear altogether.

5 Trinity refers to a specific part of the liturgical year in the ELCD. Trinity runs from the second Sunday after Pentecost until Advent. The main topic of this part of the liturgical year is the holy Trinity.

## 4.3 From basic features of language to complex cultural patterns

The study on gender and the study on biblical and cultural domains in sermons demonstrate how we can study rather complex semantic and cultural patterns in large-scale text corpora through very basic assumptions of how language works: constructing sentences revolving around agents as well as applying gender categories or names to these agents are integral features of Danish language. The taggers applied in the studies (POS and NER) testify in themselves to these assumptions: since these features are integral to language, the process of identifying agents  in  texts  can  be  automated.  The  gendered  as  well  as  named entities provide linguistic components that can be traced in the corpus in full. While we acknowledge that the individual representations of the named entities or gendered pronouns take part in many concrete and diverse contexts, we argue that the POS tagger and NER tagger allow us to investigate the larger structures that these components occur in and  their  implicit  connotations  in  the  corpus.  These  connotations provide insights into culturally significant information.

## 5. Zooming out and zooming in

In his book on practice theory, work and organisation, practice theorist Davide Nicolini describes the basic method of studying practice as a constant  process  of  zooming  in  and  zooming  out  (Nicolini  2012). Nicolini is not interested in text studies; he is concerned with field work and  careful  participant  observation.  However,  as  we  have  tried  to describe  above,  studying  a  shared  practice  from  textual  resources entails the same basic methodology - though the first step is zooming out rather than zooming in. As Moretti points out, the same kind of texts are read continuously and in our case, sermons and preaching have been studied for ages. Computational tools such as those we have used and described  are  excellent  for  creating  analytical  distance  to  a  highly studied field. Such tools allow scholars to read huge volumes of text material  focusing  on  particular  textual  features.  The  output  of  the zooming out enabled by computational tools is new kinds of texts in strange formats that now have to be read for scholars to gain research insights.  Close  reading  these  texts  entails  zooming  in  on  particular aspects of a text corpus, but for the reader to understand and interpret this,  domain-specific  competences  and  theoretical  perspectives  are needed as in any other interpretative process. These reflections resonate with  ongoing  developments  in  digital  and  computational  humanities research. In 2009, Todd Presner and Jeffrey Schnapp argued that they could detect an increasing attention to 'complexity, medium specificity, historical context, analytical depth, critique and interpretation' (Schnapp & Presner 2009:2). They described this development as the second wave of digital humanities in contrast to the first wave, which implied  a  more  narrow  understanding  of  computational  power  as primarily a helpful tool to ask new questions. With the second wave, there is an initiative to integrate tools to reconsider also epistemologically the main objective of study in humanities research, such as culture and human agency (Evans & Rees 2012). For example, Paul Baker and Tom McEnery demonstrate the convergences between corpus linguistic methods and discourse analysis (Baker & McEnery 2015). However, more theoretically encompassing attempts to define reading anew have also emerged. Literary scholar Andrew Piper uses the term 'topological reading' to define computational text analysis as a  reading  of  horizontal  networks  of  meaning  inspired  by  Deleuzian theory (Piper 2013), and more recently, appellations such as computational  hermeneutics and thick  reading have  appeared  to integrate  computational  analysis  of  text  within  a  more  traditional hermeneutical framework  in  the humanities (Mohr  et al. 2015, Fuenmayor & Benzmüller 2019). Comparatively, in the social sciences, Swedish sociologist Simon Lindgren has demonstrated how computationally informed methods align with theoretical horizons in social theory, arguing that relying on data science in other disciplines requires  that  one  dismantles  and  reassembles  in  new  ways  existing theories and methods within one's field (Lindgren 2020). We find the same to be relevant and promising in humanities research.

It  has  commonly  been  argued  that  we  are  still  lacking  well performing  computational  linguistic  tools  for  Danish  texts.  In  our process of zooming out through distant reading, we have strived to use tools that are not technically complex. We are humanist scholars and we deploy digital tools to be better humanist scholars - not to transform into digital scholars. The data retrieved with the help of these rather basic tools are quite intuitive from  a humanist perspective. The new types  of  texts  that  are  created  in  the  process  of  distant  reading  lend themselves almost seamlessly to the traditional analytical  process  of close reading  a  text. Thus,  with  this article,  we  hope  to  have demonstrated that we have been able to come a rather long way in the study  of  sermons  through  very  basic  tools.  Selecting  and  paying attention to basic functions of language across large corpora of texts allows us to uncover core structures in the sermons; and close reading these  core  structures  gives  us  new  insights  into  different  aspects  of cultural  and  religious  dynamics  in  sermons.  The  methodological pipelines  that  we  deploy  may easily be reproduced in other types of material. Close to the format that we have been working with - rather short texts meant for oral presentation - would be other types of public speeches in connection with Constitution Day, 1 May, New Year or the opening of parliament. Also, these types of speeches are both the speech of an individual person and a collective practice of public speaking on the specific occasion. However, because the digital tools that we have used are simple and because we focus on basic linguistic features, a similar approach may be used for a range of textual formats and genres. The revolution of text digitisation has indeed paved the way for even new understandings of texts and cultural practices fixed in texts. For us, the main revolution has been the creation of new challenging texts to read and interpret.

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