BIG
a) Keyness
The lemma ‘big’ was the two hundred and ninth most
significant key word in the BEC corpus.
|
N |
Word |
bec freq. |
bec.lst % |
bnc freq. |
bnc.lst % |
Keyness |
P |
|
209 |
BIG |
902 |
0.09 |
1,018 |
0.05 |
131.4 |
0.000000 |
b) Semantic Prosody
It might have been expected that
a very general word such as ‘big’ would have no clear collocative relations
with any particular words, nor any strong prosodic relations with any major
lexical sets. However, it can be seen below to collocate with at least one
large group - that of companies and institutions. It also forms part of several
adjectival/noun phrases related to business (see the colligation section
below).
Left: No clear groups identified.
Right: Three groups identified.
|
semantic prosody |
frequency/ 587
& % |
example |
|
companies/institutions |
140 - 23.85% |
big banks big business big multi-nationals |
|
money |
28 - 4.77% |
big amounts of money big bucks big fine |
|
people* |
18 - 3.06% |
big men bug guys big customers |
* some collocates here also refer to companies by using
lexis related to people, e.g. the big
players, the big boys
c) Three-word
clusters
|
N |
cluster |
Freq. |
|
1 |
of the big |
23 |
|
2 |
was a big |
12 |
|
3 |
is a big |
11 |
|
4 |
one of the |
11 |
|
5 |
have a big |
9 |
|
6 |
the big three |
8 |
|
7 |
a big impact |
7 |
|
8 |
as big as |
7 |
|
9 |
a big company |
6 |
|
10 |
all the big |
6 |
|
11 |
and the big |
6 |
|
12 |
from the big |
6 |
|
13 |
in a big |
6 |
|
14 |
make a big |
6 |
|
15 |
the big guys |
6 |
|
16 |
there was a |
6 |
|
17 |
with the big |
6 |
|
18 |
a big difference |
5 |
|
19 |
a big problem |
5 |
|
20 |
a big way |
5 |
|
21 |
for the big |
5 |
|
22 |
it's a big |
5 |
|
23 |
such a big |
5 |
|
24 |
the big money |
5 |
|
25 |
these are big |
5 |
|
26 |
a big change |
4 |
|
27 |
a big order |
4 |
|
28 |
a very big |
4 |
|
29 |
be a big |
4 |
|
30 |
be as big |
4 |
|
31 |
been a big |
4 |
|
32 |
big impact on |
4 |
|
33 |
got a big |
4 |
|
34 |
it was a |
4 |
|
35 |
made a big |
4 |
|
36 |
most of the |
4 |
|
37 |
some of the |
4 |
|
38 |
there's a big |
4 |
|
39 |
to make a |
4 |
|
40 |
to the big |
4 |
|
41 |
with a big |
4 |
d) Macro-generic
distribution

e) Colligation
COBUILD Sense 1 (a person or thing big in physical size)
51 instances - 8.51% of sample
Patterns: Adjective (graded)
big car, big computer,
a big crane
COBUILD Sense 2 (consisting of many people or things)
17 instances - 2.89% of sample
Patterns: Adjective (graded)
There is a very big
camp in Al Dunlap’s favor
big demographics
COBUILD Sense 3 (increase or change: great in degree, extent
or importance)
308 instances - 52.47% of sample
Patterns: Graded adjective
big decisions, big
gains, big impact, big problems
COBUILD Sense 4 (big organisation: corresponds mostly to
semantic prosody right category 1 above)
172 instances - 29.3% of sample
Patterns: Graded adjective
Some of the big banks
have been hit
Rugmark carpets will
be distributed by big German retailers
COBUILD Sense 5 (big in something)
1 instance - 0.17% of sample
Redland is big in
roof-tiles
COBUILD Sense 9 (a big word)
1 instance - 0.17% of sample
Patterns: Graded adjective - usually adjective-noun
There’s a big word for
you. Adjudicator.
Other COBUILD Senses:
big deal: 5
instances - 0.85% of sample
big business: 8
instances - 1.36% of sample
big name: 3
instances - 0.51% of sample
big money: 7
instances - 1.19% of sample
big time: 8
instances - 1.36% of sample
Other phrases:
(the) big picture: 4
instances - 0.68% of sample
big Apple 1
instance - 0.17% of sample
big bang: 1
instance - 0.17% of sample
Other patterns:
i) A strong tendency to form post-modified compound
nouns/adjectives:
Big Blue, big
business, big money, big players, Big Bang, the Big Three, big-time
ii) Slightly more likely to be used with an indefinite
article than a definite:
preceded by a -
160 instances - 27.25% of sample
preceded by the -
130 instances - 22.14% of sample
iii) big + on:
2 instances - 0.34% of sample
this hotel’s very big
on training
companies are getting
very big on technology
iv) (a) + big + if :
4 instances - 0.68% of sample
One of the very big
ifs is Asia
Well, you have two
very big ifs there, I think
f) Associates
|
N |
WORD |
NO. OF FILES |
AS % |
|
1 |
BIG |
8 |
100.00 |
|
2 |
BILLION |
6 |
75.00 |
|
3 |
COMPANIES |
5 |
62.50 |