In my post on Concordances and Voyant Tools, I touched on the use of corpora in discourse research. In this extended blog post, I will explore this idea further, by looking at the connectedness of critical discourse analysis (CDA) and linguistic corpora, using Sketch Engine to study two corpora, one in Spanish and the other in German.
CDA is an approach to studying written and spoken communication and the relationship between this communication and society. Van Dijk states that a central focus of CDA is “(group) relations of power, dominance and inequality and the way these are reproduced or resisted by social group members through text and talk” (van Dijk 2). It emerged from different areas of linguistics, including text linguistics and sociolinguistics, and it relates to several modules that we have studied as part of the BA World Languages programme, particularly WL2102: Introduction to Semiotics. The approach is multidisciplinary and draws on methodological approaches that are effective in examining forms of social inequality, such as inequality based on class, sexuality and religion. (Sources: Critical Discourse Analysis: Theory and Interdisciplinarity: pages 11-15, Aims of Critical Discourse Analysis)
As language forms such an important part of the approach, I wanted to closer examine how we can see power structures relevant to CDA in linguistic corpora, and thus, observe how corpus linguistics and CDA connect. I decided to focus on power structures relating to skin colour and gender, using a German-language corpus to examine skin colour and a Spanish-language corpus to examine gender.
For my investigation, I used Sketch Engine’s Word Sketch Difference feature, which compares a set of collocates for one lemma in a certain corpus to a set of collocates for another lemma within the corpus. Each lemma is given a colour (red or green) and the collocates that tend to combine with each one are given the same colour. Collocates in white tend to combine with both. If a collocate is shown in dark green or dark red, the collocation is stronger, meaning that the collocate combines far more often with the lemma of that colour and far less often with the other lemma. (Source: Word Sketch Difference lesson | Sketch Engine)
To look at group inequalities in a simple way, I decided to use lemmas that represent an opposing power relationship. It is important to note that these terms are not binary oppositions but I see them as opposing in terms of societal power structures. In the German-language corpus, I searched the lemmas ‘schwarzhäutig’ (black-skinned) and ‘weißhäutig’ (white-skinned), drawing on the amount of discrimination historically and presently faced by people of colour. In the Spanish-language corpus, I searched the lemmas ‘mujer’ (woman) and ‘hombre’ (man) based on the gender discrimination frequently experienced by women living in a patriarchal society.
The German-language corpus used was the German Web 2013 corpus (deTenTen13), which contains over 16 billion words. The Spanish-language corpus used was the Spanish Web 2018 corpus (esTenTen18), which contains over 17 billion words and two subcorpora for European Spanish and American Spanish. Both of these corpora are made up of collected web-based texts. (Sources: deTenTen – German corpus from the web | Sketch Engine, esTenTen – Spanish corpus from the web | Sketch Engine)
The result of my search can be seen here.
I decided to look at oppositions relating to skin colour in the German-language corpus for a specific reason: when using the Word Sketch Difference feature on Sketch Engine, the user can only enter a lemma. This means that one cannot enter a term such as ‘black person’ or ‘white person’. As the colours ‘white’ and ‘black’ often refer to any object with that colour, this was also not a helpful search. In German, the adjectives ‘schwarzhäutig’ (black-skinned) and ‘weißhäutig’ (white-skinned) are used, which means they can function as a lemma automatically connected to skin colour.
Although the search only results in one column due to the infrequency of the words in the corpus, this column alone gives us plenty of information. The three nouns that are shown to be modified by the adjective ‘schwarzhäutig’ six times or over and that are never modified by ‘weißhäutig’ in the corpus are ‘Hüne’ (giant/hulk), ‘Bastard’ (bastard) and ‘Afrikaner’ (African male). These collocates give us an impression of the language used in texts online around the word ‘schwarzhäutig’. The appearance of the word ‘Bastard’ shows how repeatedly negative some of this language can be. The presence of the word ‘Afrikaner’ also shows an association between black skin and African males, which is of course commonly problematic for people of colour from countries outside of Africa, as exemplified by the social media campaign by CNN ‘‘No, where are you really from?’‘.
These results contrast to ‘Amerikaner’ (American male), ‘Europäer’ (European male), ‘Fremde’ (stranger, foreign person) and ‘Blondine’ (blonde woman), which are words shown to only collocate with ‘weißhäutig’. Although these terms also show positioning of skin colour in terms of country of origin or nationality, no words such as ‘Bastard’ appear, showing the power structure.
The result of my search can be seen here.
The words ‘mujer’ and ‘hombre’ appear more frequently in the Spanish-language corpus compared to ‘weißhäutig’ and ‘schwarzhäutig’ in the German corpus.
The two verbs that mainly collocate with ‘mujer’ rather than ‘hombre’ as an object are ‘embarazar’ (to impregnate) and ‘violar’ (to violate/rape). At the bottom of the column, we can see that a verb that commonly collocates with ‘hombre’ rather than ‘mujer’ as an object is ‘armar’ (to arm). These collocates show ‘hombre’ as associated with weapons and ‘mujer’ as a receiver of violence, which shows the power structure. This is furthered when we consider the verb that mainly collocates with ‘mujer’ as a subject: ‘sufrir’ (to suffer).
By examining the column that shows collocates involving the preposition ‘sin’ (without), we can see that ‘mujer’ is associated with collocates such as ‘sin pareja’ (without a partner) and ‘sin hijo’ (without a child), which also shows certain expectations surrounding the role of women.
As a central focus of critical discourse analysis is group relations of power as shown through language, a corpus analysis can help greatly. Although my above examination of two corpora on Sketch Engine only consisted of a short investigation, it provided me with results that showed that power structures can be seen in corpora by examining collocates. In the German-language corpus, the word ‘Bastard’ showed the negativity surrounding the term ‘schwarzhӓutig’ and, in the Spanish-language corpus, ‘mujer’ was shown to receive violence and involve societal expectations surrounding partnership and children. In this sense, a corpus-based study relates to the central focus of CDA in studying the reproduction of power relations through communication. I feel that this information will be helpful for me going forward, especially as I will be taking a World Languages module next semester called WL4101: Language and Power. This task has shown me how relevant corpora are in my studies as a language student.
For more content relating to corpora and gender, please see my shorter blog essay.
List of sources:
- Sketch Engine, “deTenTen – German corpus from the web.” <https://www.sketchengine.eu/detenten-german-corpus/>
- Sketch Engine, “esTenTen – Spanish corpus from the web.” <https://www.sketchengine.eu/estenten-spanish-corpus/>
- Sketch Engine, “Word Sketch Difference lesson.” Quick Start Guide. <https://www.sketchengine.eu/quick-start-guide/word-sketch-difference-lesson/>
- van Dijk, Teun A., “Aims of Critical Discourse Analysis.” Japanese Discourse, vol. 1, 1995, pp. 17-27. <http://discourses.org/OldArticles/Aims%20of%20Critical%20Discourse%20Analysis.pdf>
- Weiss, Gilbert; Wodak, Ruth, “Introduction: Theory, Interdisciplinarity and Critical Discourse Analysis.” Critical Discourse Analysis: Theory and Interdisciplinarity, 2003, pp. 1-32. <https://www.researchgate.net/publication/304730535_Critical_Discourse_Analysis_and_Evaluative_Meaning_Interdisciplinarity_as_a_Critical_Turn>
- Zdanowicz, Christina, “No, where are you really from?” CNN, 2017. <https://edition.cnn.com/interactive/2017/08/opinion/where-im-really-from/>