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Veiling as free choice or coercion: Banal religion, gender equality, and Swedish identity on Instagram

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02 sept. 2024
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FIGURE 1

Instagram post by Ebba Busch, 22 March 2021Comments: See the Appendix for a full translation of the text in the post.
Instagram post by Ebba Busch, 22 March 2021Comments: See the Appendix for a full translation of the text in the post.

FIGURE 2

Words co-occurring with “veil” on InstagramComments: A lemmatisation is a process where different inflected forms of the same word are grouped together. As several synonyms are used alongside “veil” in the analysed debate, these are included in the co-occurrence analysis. Therefore, the word “veil” in this figure includes the following synonyms and their various inflected versions: veil [slöja], hijab [hijab], scarf [sjal], headscarf [huvudduk], and kerchief [sjalett/huckle].The analysis was performed with R and the quanteda-package, following the instructions of Wiedemann and Niekler (2017). In the analytical process, statistically significant co-occurrences of words were extracted from the analysed material. Word co-occurrences were measured by four statistics (frequency, Dice, mutual information, log-likelihood), and the effects of the statistical measures were compared. A graph network of co-occurring terms was then drawn to visualise the semantic environment of the chosen word (here: veil).
Words co-occurring with “veil” on InstagramComments: A lemmatisation is a process where different inflected forms of the same word are grouped together. As several synonyms are used alongside “veil” in the analysed debate, these are included in the co-occurrence analysis. Therefore, the word “veil” in this figure includes the following synonyms and their various inflected versions: veil [slöja], hijab [hijab], scarf [sjal], headscarf [huvudduk], and kerchief [sjalett/huckle].The analysis was performed with R and the quanteda-package, following the instructions of Wiedemann and Niekler (2017). In the analytical process, statistically significant co-occurrences of words were extracted from the analysed material. Word co-occurrences were measured by four statistics (frequency, Dice, mutual information, log-likelihood), and the effects of the statistical measures were compared. A graph network of co-occurring terms was then drawn to visualise the semantic environment of the chosen word (here: veil).