Comparing EDL Discourses Using Word Clouds

For this post I’ve used an online visualization software called ‘TagCrowd’ available at http://tagcrowd.com/

 

I’m interested in how texts created by EDL leaders differ from those of members who post on their Facebook page and used  a visualization software to help with this.

The first image is the word cloud created from a corpus of EDL texts.

edl word cloud

The second image was created using texts from EDL supports who posted on the groups Facebook page.

edl-fb word cloud

 

By comparing and contrasting these two images, it is possible to observe discourse topics, although not what is being said about the particular themes. It appears that both corpora contain discourses related to islam, muslims, edl, british, halal country and government. There appears to be differences also. Certain words caught my attention among the many differences between the two images. The EDL corpus contains discourses related to topics such as extremism, radical, sharia, terrorism and community. Such words were not significant in the Facebook corpus. However, the Facebook corpus contained discourses which were not prominent in  the EDL corpus. These include racist, hate, white, grooming, scum, kids, girls children, women and sex.

Although it is not possible to gain conclusive evidence of the discourses present in the corpora, it does appear that the EDL hierarchy are more concerned with issues related to Islamic extremism and terrorism. The corpus of Facebook text contains discourses related to family, race, and conflict (abuse, bad, grooming, hate, idiot, kill, racist, rape, scum).

Although the text contain fundamental similarities, there are also significant differences.

  

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2 thoughts on “Comparing EDL Discourses Using Word Clouds

  1. Just out of interest, what texts make up the EDL corpus?

    Is it transcriptions of speeches, their own ‘news’ reports on their websites, transcriptions of TV interviews (Newsnight, etc.) or a combination?

  2. I used two sources to collect the data. I built one corpus from texts published on the EDL’s official website (from the ‘news’ section), the second corpus was compiled of texts from the EDL’s Facebook page.

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