MERGER

 

 

a) Keyness

 

The lemma ‘merger’ was the one hundred and fifty-fifth most key word in the BEC corpus.

 

N

Word

bec freq.

bec.lst %

bnc freq.

bnc.lst %

Keyness

P

155

MERGER

233

0.02

107

-

165.2

0.000000

 

 

b) Semantic Prosody

 

Left: Four groups identified.

 

semantic prosody

frequency/168 & %

example

size/money

16 - 9.52%

biggest-ever merger

mega-merger

$23 billion merger of ...

companies/institutions

29 - 17.26%

a green light to the AMEX merger

a banking and insurance merger

time

12 - 7.14%

in the midst of a merger

pre-merger success

possibility

6 - 3.57%

a potential merger

the proposed merger

 

Right: No main groups identified but see the colligation section below.

 

 

c) Three-word clusters

 

N

cluster

Freq.

1

the merger of

7

2

of the merger

6

3

a merger of

5

4

and grand metropolitan

4

5

Guinness and grand

4

6

merger of the

4

7

the merger and

4

8

the merger between

4

 

 

 

 

 

d) Macro-generic distribution

 

 

 

e) Colligation

 

Only 1 sense given in COBUILD (joining together of two separate companies)

100% of sample

Patterns: Count noun

 

Other patterns:

 

i) merger + between/merger + of : (these usually name both parties of the merger or at least infer the presence of the two parties)

33 instances - 19.64% of sample (11 between, 22 of)

merger between UniChem and Alliance, merger between Waterstone’s and Dillon’s

a merger of the two...

 

 

ii) merger + with: (usually names both parties)

15 instances - 8.92%

 

 

 

f) Associates

 

N

WORD

NO. OF FILES

AS %

1

MERGER

12

100.00

2

BILLION

7

58.33

3

COMPANIES

5

41.67