[Solution]Assignment 3: Doing Discourse Analysis using NVivo

Report Length: 1750 words maximum plus citations of course readings. In this assignment you will analyze a current issue of relevance to the discussion of…

Report Length: 1750 words maximum plus citations of course readings.
In this assignment you will analyze a current issue of relevance to the discussion of
race and ethnicity by using critical discourse analysis to examine messages
contained in a newspaper articles (online or hard copy).
In order to complete this assignment, you will need to access the NVIVO software.
In addition to working with NVivo, you will also need to produce a written
assignment that answers the questions listed throughout these instructions. As you
answer these questions, please make reference to the course readings. Use proper
citation and bibliography formatting in your report. Submit both your written work
and your NVivo project file to your TA via Canvas for grading (further details on
submission formats and types of files will be provided by your TA).
1) Getting Started
Gather the newspaper articles that you will use for your discourse analysis.
a) Once again, start by gathering your documents. This time, you can choose from
a list of articles that will be provided by Daniel. This list is complied based on
topics that has been in the news about the issue of race and ethnicity in the past
year or so, some with global focus, others with more local focus. For each issue,
there will be 2 articles with two different viewpoints on the issue. Your task is to do
a discourse analysis of both articles.
b) Think about the theory of media framing and how media represents a version of
reality. That version is neither correct nor wrong; rather it’s a way for media to
represent and frame reality. Your task is to analyze two articles that represent “two
sides a story,” typically one “pro” side and an “anti” side. There is a broad range of
topics that you can focus on when it comes to the issue of race and ethnicity. Here’s
a short inventory of broad topics:
• The refugee crisis (both in terms of how it is covered in the Canadian context,
and abroad).
• Donald Trump’s various comments regarding Mexicans, Muslims, refugees,
illegal immigrants, undocumented immigrants, etc.
• The impact of foreign buyers/foreign money on Vancouver’s real estate
market.
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c) Open a new blank file in NVIVO. Create a new Folder for your articles. Right click
on Internals->New Folder. Call this new folder ‘Discourse Analysis’.
d) With your Discourse Analysis folder selected, click the data tab near the top of the
screen. NVivo obliges you to import documents by file type. So, for example, to
import a PDF, select Data->PDF. Give a name to your file and hit ‘done’.
Pro Tip: You can also import your documents using NCapture, which is an NVivo
extension in Google’s Chrome Web Browser. If you are using Chrome to surf the
internet, and if it has the NCapture Extension at the top right of the screen, then you
can automatically capture websites for import into NVivo. Go to the webpage you
want to capture and click the NCapture button. It looks like this: . A dialogue
window will pop up. Make your selections and click capture. Now open N-Vivo and,
with the Discourse Analysis folder selected, go to the data tab. Click NCapture. A
new window will appear with a list of your captured websites. Now you can import
your news articles.
Select the Discourse Analysis folder that you created under Internals. You can now
open and read your news article right in NVivo by double clicking on the title of the
document in the file list. You can close the document again by closing the tab (in
Windows) or closing the items in the Open Items list, which is at the bottom left of
your screen (on Mac).
Question 1: Describe the current issue that you are going to analyze. Explain the
logic of your comparison. For example, are you comparing content in articles
published with different audiences in mind? Or are the intended audiences the same
for both articles? Why does that matter?
Question 2: Explain your methodological toolbox (i.e., discourse analysis) and the
properties of text and context that you will be focusing on for your analysis (See the 3
readings by van Dijk, Mautner, and Weintraub for their discussion of a methodological
toolbox for doing discourse analysis). (Tip: You will not be able to look at all properties
of text and context that they describe, but the assignment, as you see below, directs you
to a very specific method of analysis which involves choosing a word and looking at the
lexical properties of the word and its association to other words in the news articles
analyzed).
2) Word Frequency Query
Use the Query function to analyze word frequency in your news articles.
a) Click the Query tab at the top of the screen and select ‘Word Frequency.’ A new
window will appear. In order to focus on the frequency of words in your newspaper
articles, click on ‘Selected Items’. (If you skip this step, you will get the word
frequency of all of your documents, including documentary artifacts from
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Assignment 1, if you are working in the same document.) A new window will pop
up. Select Internals->Discourse Analysis and select the documents that you want to
query. Next select ‘Include stemmed words’ and in the Display Words window. This
will ensure that similar words (time, times, timing) will be grouped together.
Finally, reduce the frequency from 1000 to 25. Once you’ve done all of this, click
‘Run Query’.
b) Take a look at your word list. You may want to suppress some of the words that
appear in this list. For example, if you downloaded your articles from a news
website, the query will include the navigation prompts from the website, which
aren’t really part of the article. To suppress these words from your query, right click
on the word, and select ‘Add to Stop Words List.’ Once you have done this, click ‘Run
Query’ again.
c) Once you are happy with your word frequency list, save your query. Click ‘save
query’ on the right-hand side of the screen and name your query ‘Word Frequency.’
Your query will be stored under Queries on the left hand menu bar. You can run it
again whenever you like. (NVivo saves the query, not the results of the query, in
case you decide to change your source documents later on.)
d) Look at your word list again. Identify a word (i.e. a ‘text’) that you think deserves
further analysis. (For example, when I was putting together this assignment, I
gathered articles about the foreign buyers tax implemented by Premier Christy
Clark in July 2016. The word ‘foreign’ was an important and provocative word in
my list.) Right click on your chosen word, and click ‘Run Text Search Query’ in the
dropdown menu. This will produce a list of all the newspaper articles where the
word foreign appears. Double click the article to open it up; the word foreign is
highlighted each time that it appears.
e) Take note of whether your word appears in all of your articles or not.
Question 3: What word did you choose and why? Think back to Fairclough: Is your
word a ‘text’ or a ‘discourse’? Explain. What could the frequency of appearance of a
word mean/imply?
3) Coding
NVivo allows you to create ‘nodes’ that gather chunks of text together. Nodes are
like buckets that collect examples of the different discourse practices that you
observe. By creating buckets of examples, you can start to identify discourse
patterns.
a) Take a closer look at the news articles with highlighted words that you produced
in step 2 above. Your key word is probably used in slightly different ways each time
that it appears. (For example, in my analysis of the foreign buyers tax, I found
foreign buyer, foreign citizen, foreign cash, etc. Use of the word foreign differed in
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subtle ways from one sentence or article to the next.). Your goal now is to sort these
different references into categories so that you can detect patterns.
Select the relevant text around each key word and right click on your highlighted
text (note that the text you will select can be a word which appears
immediately before or after your key word, or a sentence or two that comes
before or after your key word). Select Code Selection->At New Node in the
dropdown menu. Give your Node a name. (For example, I coded “the issue of
foreign buyers” as ‘foreign: negative’.) Repeat this process for each highlighted
word that appears in the text. If your selection fits into a Node that you have
already produced, then code that reference to an existing Node. If the reference is
unlike what you’ve seen before, then create a new Node.
It is helpful to pick nodes that will allow you to characterize your articles. For
example, you might decide to code your data into positive, neutral and negative
buckets. In this way you can begin to assess whether your documents are mostly
leaning one way or another.
b) Your key concept may appear in other ways as well. For example, the word thief
may also appear as robber or crook. Read through your articles to find any
additional references to your key concept, and code these as well using existing or
new Nodes as required. (For example, besides foreign, in my articles I also found
the phrase “investment by Chinese nationals is a threat” which I coded as ‘foreign:
negative’.)
c) You can view the content of your nodes by selecting ‘nodes’ under the Nodes
menu on the left side of your screen. When you double click on a node, you will see
every chunk of text that you dumped into that node. You can now use these lists to
identify patterns in the way that your key concept is presented across all the
articles.
Question 4: What patterns do you observe in the use of your key ‘text’?
4) Making Connections: Matrix Comparisons
a) Go to nodes under the Nodes menu and open up each of your buckets of text.
Copy and paste this material into your report. Organize the contents of your nodes
into a matrix the compares the portrayal of your key term across your articles. (For
example, if you have two articles and two nodes, then you will produce a 2×2 table
that has articles on one axis and nodes on the other axis.) Here is an example:
Table 1: Matrix Comparison of Discourses against Newspaper
Foreign: Positive Foreign: Negative
Vancouver Sun “investment by Chinese
nationals is a threat”
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The Toronto Star “foreign buyers inject resources
into our community”
As you do this work, feel free to add comments into your matrix. For example, you
may wish to add observations about the ways in which certain words are used in a
sentence (discursive practices).
Question 5: Do you notice any pattern in the allocation of discourses across your
cases? How so? (Remember that no pattern is also a pattern.)
Question 6: In assignment 1 you compiled information about each of your cases from
your documentary materials. Think back at that exercise. Do these documents from
Assignment 3 provide any background information (context) that helps explain the
observed patterns? What might this suggest about the journalistic practices of these
sources and their wider social implications? Note: You may have to do some
background research to find out more about the sources of your documents and their
editorial mandate.
Question 7: Think back to your answers to questions 1, 2 & 3. Is it possible to draw
conclusions about discourse affects based on the work that you did in this assignment?
Why or why not?
5) Handing in your Work
Save your report as a PDF and upload both your report AND your NVivo file using
the Assignments link in Canvas.
 

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