In a recent post (How To Cut Thousands of Words Without Shedding A Tear) Rachelle Gardner discusses strategies for reducing the word count of a finished manuscript. The post is worth reading because of the useful suggestions it contains, but I was surprised that none of the 140+ responses mentioned the issue of word frequency, so I decided to highlight it here.
Every author overuses certain words, either because those are words he particularly likes or because they are especially relevant to the manuscript (or for any other reason.) I became aware of this problem years ago, when working on a non-fiction manuscript that had to use words for which synonyms either did not exist or were difficult to find. Searching for a solution to this problem I discovered that several programs had been developed to tabulate the frequency in which a word appears in a text. The one I like best, which is very useful and easy to use, is free and can be downloaded at: http://wordfrequency.codeplex.com/
To use it you paste your manuscript into the program window and it calculates how many times each word appears in it. The program displays a list of words and their frequency. Inspecting the list of words with high frequency will tell you if you have been overusing any of them.
The image below shows how the program analyzed this post.
I exported the result to an excel sheet (see the table at the bottom of this post) and organized it by decreasing word frequency. I am now able to see clearly which words were overused, to look for them in the manuscript and to substitute some of them with synonyms or to delete them.
Go ahead and start tightening!
Kfir
|
Word |
in this doc |
Total |
|
to |
12 |
12 |
|
the |
11 |
11 |
|
of |
10 |
10 |
|
a |
8 |
8 |
|
words |
6 |
6 |
|
I |
6 |
6 |
|
and |
6 |
6 |
|
word |
5 |
5 |
|
manuscript |
5 |
5 |
|
it |
5 |
5 |
|
frequency |
5 |
5 |
|
for |
5 |
5 |
|
which |
4 |
4 |
|
this |
4 |
4 |
|
them |
4 |
4 |
|
The |
4 |
4 |
|
post |
4 |
4 |
|
or |
4 |
4 |
|
in |
4 |
4 |
|
you |
3 |
3 |
|
useful |
3 |
3 |
|
use |
3 |
3 |
|
that |
3 |
3 |
|
program |
3 |
3 |
|
is |
3 |
3 |
|
because |
3 |
3 |
|
with |
2 |
2 |
|
were |
2 |
2 |
|
was |
2 |
2 |
|
To |
2 |
2 |
|
synonyms |
2 |
2 |
|
see |
2 |
2 |
|
problem |
2 |
2 |
|
list |
2 |
2 |
|
into |
2 |
2 |
|
how |
2 |
2 |
|
had |
2 |
2 |
|
either |
2 |
2 |
|
below |
2 |
2 |
|
been |
2 |
2 |
|
appears |
2 |
2 |
|
any |
2 |
2 |
|
your |
1 |
1 |
|
years |
1 |
1 |
|
worth |
1 |
1 |
|
working |
1 |
1 |
|
Words |
1 |
1 |
|
wordfrequency |
1 |
1 |
|
Without |
1 |
1 |
|
window |
1 |
1 |
|
will |
1 |
1 |
|
when |
1 |
1 |
|
very |
1 |
1 |
|
times |
1 |
1 |
|
Thousands |
1 |
1 |
|
those |
1 |
1 |
|
their |
1 |
1 |
|
Thanks |
1 |
1 |
|
text |
1 |
1 |
|
tell |
1 |
1 |
|
tear |
1 |
1 |
|
tabulate |
1 |
1 |
|
surprised |
1 |
1 |
|
suggestions |
1 |
1 |
|
substitute |
1 |
1 |
|
strategies |
1 |
1 |
|
some |
1 |
1 |
|
solution |
1 |
1 |
|
so |
1 |
1 |
|
shows |
1 |
1 |
|
sheet |
1 |
1 |
|
Shedding |
1 |
1 |
|
several |
1 |
1 |
|
Searching |
1 |
1 |
|
result |
1 |
1 |
|
responses |
1 |
1 |
|
relevant |
1 |
1 |
|
reduce |
1 |
1 |
|
recent |
1 |
1 |
|
reason |
1 |
1 |
|
reading |
1 |
1 |
|
Rachelle |
1 |
1 |
|
programs |
1 |
1 |
|
paste |
1 |
1 |
|
particularly |
1 |
1 |
|
overusing |
1 |
1 |
|
overuses |
1 |
1 |
|
overused |
1 |
1 |
|
other |
1 |
1 |
|
organized |
1 |
1 |
|
one |
1 |
1 |
|
on |
1 |
1 |
|
now |
1 |
1 |
|
not |
1 |
1 |
|
none |
1 |
1 |
|
non |
1 |
1 |
|
mentioned |
1 |
1 |
|
me |
1 |
1 |
|
many |
1 |
1 |
|
look |
1 |
1 |
|
line |
1 |
1 |
|
likes |
1 |
1 |
|
like |
1 |
1 |
|
let |
1 |
1 |
|
know |
1 |
1 |
|
Kfir |
1 |
1 |
|
issue |
1 |
1 |
|
Inspecting |
1 |
1 |
|
In |
1 |
1 |
|
image |
1 |
1 |
|
if |
1 |
1 |
|
If |
1 |
1 |
|
http |
1 |
1 |
|
How |
1 |
1 |
|
highlight |
1 |
1 |
|
high |
1 |
1 |
|
here |
1 |
1 |
|
he |
1 |
1 |
|
have |
1 |
1 |
|
Gardner |
1 |
1 |
|
free |
1 |
1 |
|
finished |
1 |
1 |
|
find |
1 |
1 |
|
fiction |
1 |
1 |
|
exported |
1 |
1 |
|
exist |
1 |
1 |
|
excel |
1 |
1 |
|
Every |
1 |
1 |
|
especially |
1 |
1 |
|
easy |
1 |
1 |
|
each |
1 |
1 |
|
drop |
1 |
1 |
|
downloaded |
1 |
1 |
|
displays |
1 |
1 |
|
discussed |
1 |
1 |
|
discovered |
1 |
1 |
|
difficult |
1 |
1 |
|
did |
1 |
1 |
|
developed |
1 |
1 |
|
delete |
1 |
1 |
|
decreasing |
1 |
1 |
|
decided |
1 |
1 |
|
Cut |
1 |
1 |
|
count |
1 |
1 |
|
contains |
1 |
1 |
|
com |
1 |
1 |
|
codeplex |
1 |
1 |
|
clearly |
1 |
1 |
|
certain |
1 |
1 |
|
can |
1 |
1 |
|
calculates |
1 |
1 |
|
by |
1 |
1 |
|
but |
1 |
1 |
|
best |
1 |
1 |
|
became |
1 |
1 |
|
be |
1 |
1 |
|
aware |
1 |
1 |
|
author |
1 |
1 |
|
at |
1 |
1 |
|
are |
1 |
1 |
|
analyzed |
1 |
1 |
|
an |
1 |
1 |
|
am |
1 |
1 |
|
ago |
1 |
1 |
|
able |
1 |
1 |
|
A |
1 |
1 |
|
140 |
1 |
1 |
What an interesting post! I probably use "writer" too often in my reviews. :]