Using%20corpora%20in%20critical%20discourse%20analysis

1
Using corpora in critical discourse analysis

• Corpus Linguistics
• Richard Xiao
• lancsxiaoz_at_googlemail.com

2
Aims of this session

• Lecture
• Corpora versus critical discourse analysis
• The state of the art of corpus-based discourse
  studies
• Case study How is Islam constructed in the UK
  and US press before and after 9/11?
• Lab session
• Using Wmatrix to exploring political discourse
  Michael Howard and Tony Blairs farewell speech
  to their party

3
Critical discourse analysis (CDA)

• Discourse
• Language use above the sentence level
• Language use in context
• Real language use
• CDA examines language as a form of cultural and
  social practice, focusing on the relationship
  between power and discourse, and between language
  and ideology

4
CL vs. CDA

• Both rely heavily on real language
• a cultural divide (Leech 2000 678-680)
• CDA emphasizes the integrity of text while CL
  tends to use representative samples
• CDA is primarily qualitative while corpus
  linguistics is essentially quantitative
• CDA focuses on the contents expressed by language
  while CL is interested in language (form) per se
• The collector, transcriber and analyst are often
  the same person(s) in CDA while this is rarely
  the case in CL
• The data used in CDA is rarely widely available
  while corpora are typically made widely available

5
A diminishing divide

• Some important points of contact (McEnery and
  Wilson 2001 114)
• The common computer-aided analytic techniques
• The great potential of standard corpora in CDA as
  control data

6
Use of corpora in CDA pros and cons

• Cons
• The corpus-based approach tends to obscure the
  character of each text as a text and the role
  of the text producer and the society of which
  they are a part (Hunston 2002 110)
• CL focuses on text, not text producer
• Analyzing a lot of text from a corpus
  simultaneously would force the analyst to lose
  contact with text (Martin 1999 52)
• Pros
• Corpora present a real opportunity to discourse
  analysis, because the automatic analysis of a
  large number of texts at one time can throw into
  relief the non-obvious in a single text
  (Partington 2003 7)

7
Use of corpora in CDA pros and cons

• Pros
• Obviously, the methods for doing a critical
  discourse analysis of corpus data are far from
  established yet. Even when we have examined a
  fairly large set of attestations, we cannot be
  certain whether our own interpretations of key
  items and collocations are genuinely
  representative of the large populations who
  produced the data. But we can be fairly confident
  of accessing a range of interpretative issues
  that is both wider and more precise than we could
  access by relying on our own personal usages and
  intuitions. Moreover, when we observe our own
  ideological position in contest with others, we
  are less likely to overlook it or take it for
  granted. (de Beaugrande 1999 287)

8
CL and CDA interaction and synergy

• Partington (2003 12) proposes a scalar view of
  the uses of CL, pointing towards a rationale for
  using CL-related methods to carry out CDA
• At the simplest level, corpus technology helps
  find other examples of a phenomenon one has
  already noted. At the other extreme, it reveals
  patterns of use previously unthought of. In
  between, it can reinforce, refute or revise a
  researchers intuition and show them why and how
  much their suspicions were grounded.
• Partington (2004, 2006) provides a systematic
  description of CADS (corpus-assisted discourse
  studies)

9
CL and CDA interaction and synergy

• Complementary to each other and interaction
  benfiting both areas of research
• CL can provide a general pattern map of the
  data, mainly in terms of frequencies, key
  words/clusters and collocations, as well as their
  diachronic development (the latter contributing
  to the historical perspective in DHA Discourse
  Historical Approach represented and pioneered by
  Ruth Wodak), which helps pinpoint specific
  periods for text selection or sites of interest
• The CDA analysis can point towards patterns to be
  further explored through the CL lens and also
  provide explanations for corpus findings

10
CL and CDA interaction and synergy

• CL can also examine frequencies (or at least
  provide strong indicators of the frequency) of
  specific phenomena recognized in CDA (e.g.,
  topoi, topics, metaphors) by examining lexical
  patterns
• CL can add a quantitative dimension to CDA to
  make it more objective
• CL in general and concordance analysis in
  particular can be positively influenced by
  exposure and familiarity with CDA analytical
  techniques

11
CL and CDA interaction and synergy

• CL needs to be supplemented by the close analysis
  of selected texts using CDA theory and
  methodology
• CDA, in turn, can benefit from incorporating more
  objective, quantitative CL approaches, as
  quantification can reveal the degree of
  generality of, or confidence in, the study
  findings and conclusions in CDA

12
Possible stages in CADS
Baker et al (2008 295)
13
Construction of Islam in UK and US press around
9/11

• How do news stories construct Islam?
• Have there been any changes before and after
  9/11?
• Are there differences between reporting on Islam
  (as a religion) and Muslims (as a people)?
• Are there any differences/similarities between
  tabloids and broadsheets?
• Are there any differences/similarities between
  American and British newspapers?

14
Why Islam?

• Post WWII demand for unskilled labour results
  in migration of Pakistani and Bangladeshi Muslims
  to the UK
• In April 2001 the former British Foreign
  Secretary Robin Cook reported that Britains
  national dish is chicken tikka masala
• September 2001 terrorist attacks on the US,
  believed to be associated with Islamic extremists
• July 2005 terrorist attacks on UK

15
Data

• UK and US newspapers in 1998-2005 (pre- and
  post-9/11)
• 87 million words of British news
• Broadsheets (65 M words) The Business, The
  Guardian, The Independent Independent on
  Sunday, The Observer, The Times Sunday Times,
  Daily Telegraph Sunday Telegraph
• Tabloids (22 M words) The Daily Express Sunday
  Express, The Daily Mail Mail on Sunday, Daily
  Mirror Sunday Mirror, The People, Daily Star
  Sunday Star, The Sun
• 40 million words of American news
• Financial Times, New York Times, Washington Post,
  San Francisco Chronicle

16
Search terms related to Islam

• Alah OR Allah OR ayatolah OR burka! OR burqa! OR
  chador! OR fatwa! OR hejab! OR imam! OR islam! OR
  Koran OR Mecca OR Medina OR Mohammedan! OR
  Moslem! OR Muslim! OR mosque OR mufti! OR
  mujaheddin! OR mujahedin! OR mullah! OR muslim!
  OR Prophet Mohammed OR Q'uran OR rupoush OR
  rupush OR sharia OR shari'a OR shia! OR shi-ite!
  OR Shi'ite! OR sunni! OR the Prophet OR wahabi OR
  yashmak! AND NOT Islamabad AND NOT shiatsu AND
  NOT sunnily

17
Frequencies of articles over time
2011-09
18
Method

• Corpora split into 4
• All sub-corpora compared to a reference corpus
  (BNC written 90 million words)
• 3. UK sub-corpora compared with US sub-corpora
• 4. Keywords extracted and analysed via
  concordances with respect to moral panic
  categories
• 5. UK broadsheets vs. UK tabloids
• 6. Collocational and concordance analysis of
  Islam, Islamic, Muslim, Muslims

UK pre 9/11 (27 million) US pre 9/11
UK post 9/11 (60 million) US post 9/11
19
Moral panic

• Conceived by Stanley Cohen (1972) in his study of
  Mods and Rockers in the UK
• Violent clash between the gangs of Mods and
  Rockers in 1964
• Two conflicting British subcultures in the mid
  1960s
• Referring to the intensity of feeling expressed
  by a large number of people about a specific
  group of people who appear to threaten the social
  order at a given time

20
Features of moral panic

• Build-up of concern over a social issue
• A scapegoat (social group)
• Solutions proposed moral entrepreneurs
• A person who seeks to influence a social group to
  adopt or maintain a norm, e.g. MADD (mothers
  against drunk driving), and the anti-tobacco
  lobby
• Moral panic is often expressed as outrage rather
  than fear
• Emotive language is used
• Threat is normally exaggerated

21
McEnerys (2005) moral panic categories

• 1. object of offence
• that which is identified as problematic
• 2. consequence
• the negative results which it is claimed will
  follow if the object of offence is not eliminated
  
• 3. corrective action
• the actions to be taken to eliminate the object
  of offence

22
McEnerys (2005) moral panic categories

• 4. desired outcome
• the positive results which will follow from the
  elimination of the object of offence
• 5. moral entrepreneur
• the person/group campaigning against the object
  of offence
• 6. scapegoat
• that which is the cause of, or which propagates
  the cause of offence
• 7. rhetoric
• register marked by a strong reliance on
  evaluative lexis that is polar and extreme
  (strong language)

23
UK keywords pre 9.11

• No evidence of moral panic
• References to Iraq, Israel, Kosovo, Palestine
• Muslims often mentioned in passing rather than
  as main subject of article
• A wider range of contexts pre 911
• fashion, famous, tourists, music, hotel, cricket,
  sex, leisure, dance, ski, museum, divorce, café,
  wine, gardens, film, beer, holidays, football,
  exotic, fun

24
UK - After 9/11

• British Muslims and what they believe
• The vast, vast majority, of Muslims living in
  the UK support policing efforts, fear terrorism
  and want to work with us," said Sir Ian. (The
  Guardian, October 29, 2004).
• Focus on belief
• moderate, militants, fanatics, fundamentalist,
  extremists
• Focus on immigration, political correctness and
  scroungerphobia (taxpayers)

25
UK moral panic post 9/11?
Category Positive Keywords in that Category
Consequence anger, angry, bad, bombing, bombings, conflict, crime, dead, death, destruction, died, evil, fear, fears, injured, kill, killed, killing, murder, terror, threat, victims, violence, wounded, wrong
Corrective action arrested, fight, fighting, invasion, jail, justice, moderate, occupation, police, revenge, troops
Desired outcome best, better, freedom, good, peace, support
Moral entrepreneur America, American, Britain, British
Object of offence atrocities, attack, attacks, bomb, bombs, criminal, extremism, failed, hatred, illegal, jihad, radical, regime, terrible, terrorism, weapons
Scapegoat Arab, (suicide) bombers, enemy, extremists, immigrants, Iran, Iraq, Iraqi, Islam, mosque, Muslim, Muslims, Pakistan, Palestinian, religious, suicide, terrorists
Rhetoric question, need, must, why
26
US before 9/11

• Keywords are mainly proper nouns relating to
  Israel/Palestine, Bosnia, Kosovo, Indonesia.
• Peace is a keyword focus on contexts where
  Muslims are aggressed against
• Muslims (occasionally cast as internal to the US)

27
US keywords post 9/11
Consequence attacks, Sept
Corrective action American, Americans, forces, intelligence, marine, marines, military, officials, (war on) terror, war (on terror)
Desired outcome NONE
Moral entrepreneur Bush, pentagon, United States, US
Object of offence Terrorism
Scapegoat (al) Qaeda, afghan, Afghanistan, al (Qaeda), bin (laden), (Saddam) Hussein, Husseins, insurgents, Iraq, Iraqs, Iraqi, Iraqis, (bin) Laden, Saddam (Hussein), Shiite, Shiites, Sunni, Taliban, terrorist, terrorists,
Rhetoric NONE
28
Tabloids vs. Broadsheets

• Style and spelling
• Tabloids (chatty, interactive style)
• Pronouns I, my, me, myself, we, he, she
• Emphatic adjectives stunning, fantastic,
  terrible, wonderful
• Broadsheets (logical, formal, nouny style)
• Conjunctions/determiners the, that, which
  however, thus, than
• Formal terms of address Mr, Ms

29
Moslem key in the tabloids

• 7,282 tabloid uses
• 4,834 in the Daily Mail
• 2,208 Daily Express

30
Bin Laden in tabloid newspapers

• powerful (mastermind, terrorist godfather,
  millionaire, Al Qaeda leader)
• warrior leader (chief, warlord)
• outcast (dissident, exile, fugitive)
• insane (maniac, twisted)
• evil (gloating menace, evil, terrorist,
  murderous)
• fanatical (extremist, fanatic, fanatical)

31
Tabloid villains

• Direct references to terrorist attacks
• terror, terrorists, Taliban, Osama, Bin, Laden,
  bomb, bombs, bomber, bombers, plane, suicide,
  killers, attack, crash, hijack, September, twin
  and towers
• Emotive/evaluative reaction emotionally charged
  lexis
• atrocity, atrocities, tragedy, carnage, horror,
  terrible, evil

32
Other tabloid categories

• Brainwashing
• lure, rant, rants, spew, rouser, brainwashed
• Children are being brainwashed into becoming
  Islamic extremists at 300 "Taliban schools" in
  Britain, it was reported last night. Youngsters
  are being indoctrinated with radical Islamic
  ideals by militant groups across the country,
  said leading British Muslim Dr Zaki Badawi.
  (The Sun, December 28, 2001)
• Also, scrougerphobia and political correctness

33
Types of belief in tabloid vs. broadsheet

• In the tabloids, Muslims are fanatics and
  extremists
• In the broadsheets, Muslims are radicals,
  fundamentalists, separatists but also moderates
  and progressives

34
Broadsheet keywords

• More focus on Islam
• The media book, novel, television, film, poetry
• Other religions Hindu, Christian, Buddhist,
  Judaism
• World events Iran, Iraq, Iraqi, Arab, Israeli,
  Israel, Palestinian, Baghdad, Jerusalem, Lebanon,
  Syria
• War and conflict military, conflict, army,
  resistance, violence, occupied, ceasefire,
  genocide, peace, invasion

35
Muslim(s) vs. Islam(ic)

• Tabloids more focus on Muslims (the people)
• Muslims as terrorists evil preachers, Muslims as
  British and desiring peace, women as victims
  (honor killings, arranged marriage, hijab), men
  as potential terrorists or victims of racism
• Broadsheets more focus on Islam (as a religion)
• Stories on terrorism restricted to the word
  Islamic

36
Political discourse Howard vs. Blair

• Use Wmatrix to tag the following two texts
• Tips Its a good practice to create one folder
  for each file
• Michael Howards farewell speech to his party
  (2005)
• Leader of Conservative Party in 2003-2007
• Tony Blairs farewell speech to his party (2006)
• Leader of Labour Party in 1997-2007

37
A quick how to!

• Enter new workarea name (Blair / Howard)
• Click the browse button to select the right file
• Click the upload now button
• A new screen will provide you with an update
  report e.g.

part of speech tagging semantic tagging
frequency lists
38
You will then be taken to your work areaMy
folders
39
What youll see in the Simple VIEW of folder
Click on Frequency to see the most frequent
words what are they?
You can also do concordance searches of
words/phrases
Scroll down to see Tag clouds - key concepts
--- and investigate Word clouds ( the most key
words)
40
The word cloud of Howards farewell speech
(compared with Blair)
41
We use a similar method to investigate keywords
(as with WordSmith)
with text B
i.e. we compare text A
and not only the frequent items
so that we can discover the most significant
items within text A
42
Exploring keywords (as word clouds) in simple view
- and any keywords with LL15 will appear
Under 3. Word clouds, scroll down the pop-up
menuto choose Blair Then click on Go
43
Advanced View of Howard Folder
Click on Frequency to see the most frequent words
(as before)
--- and investigate key parts of speech (POS)
and key concepts / domains
How might we discover the most frequent POS?
Jot them down
and the most frequent semantic fields? Make a
note of them
We can also see all of the keywords using this
VIEW
44
Frequency of words in Howard and Blair (using
advanced view)
Make a note of the similarities and differences
45
Exploring keywords using advanced view

• Find the key words compared to drop-down
  menu, and click Go

You will be taken to a web-page, which shows ALL
keywords
46
Keywords for Howard (when compared with Blair)

• IMPORTANT
• anything above LL 15 99.99 confidence of
  significance
• anything above LL 6.63 99 confidence of
  significance
• How many keywords from the Howard text have LL
  values of 15? What are they?
• How many keywords have LL values of 7? What are
  they?
• Do you notice anything interesting about these
  keywords?
• Do any of the keywords share the same semantic
  fields?

47
Same procedure for key POS and key domains

• Find the key POS compared to drop-down menu,
  and click Go

Find the key concepts compared to drop-down
menu, and click Go
48
Exploring key domains (Howard, in comparison to
Blair)

• What do you notice about the key domains?
• Do we capture more words by undertaking a key
  domain analysis than we do by undertaking a
  keyword analysis? And, if so, why do you think
  this is the case?
• Undertake a keyword analysis of Blair (using
  Howard as the reference corpus) to determine the
  differences between the two speeches