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