Methodology
Cut responce text (unedited) out of spreadsheet and into text file, then into wordle. Get word frequencies, and copy/paste to excell. Eliminate common pronouns and prepositions. Cut off words with frequency less than 10. At this point, there were ~11% more against words than for words, so frequencies were normalized. Against words were reculled at 11, and normalization was redone (it changes by less than 2%). For and Against totals were subtracted from one another, and wordles were made from both sides for whichever had more of a given word.
Note that I have left many common words in to see if their frequency is different between the two camps.
Against:
For:
Against data:
word | against diff |
---|---|
ABLE | 0 |
ABORTION | 13 |
ABOUT | 13 |
ACCESS | 0 |
AFFORD | 0 |
AFFORDABLE | 0 |
ALL | 0 |
ANY | 0 |
ANYTHING | 15 |
ARE | 0 |
AS | 0 |
AT | 0 |
BECAUSE | 0 |
BELIEVE | 7 |
BETTER | 0 |
BILL | 27 |
BUT | 0 |
BY | 11 |
CAN | 0 |
CAN'T | 0 |
CARE | 0 |
CHANGE | 0 |
CHILDREN | 0 |
COMPANIES | 0 |
CONTROL | 3 |
COST | 43 |
COSTS | 23 |
COUNTRY | 0 |
COVERAGE | 0 |
DO | 14 |
DOESN'T | 14 |
DONE | 1 |
DON'T | 97 |
ECONOMY | 16 |
EVEN | 0 |
EVERYBODY | 0 |
EVERYONE | 0 |
EXPENSIVE | 4 |
FOR | 0 |
FREE | 11 |
GET | 0 |
GO | 10 |
GOING | 48 |
GONNA | 13 |
GOOD | 6 |
GOVERNMENT | 87 |
HAS | 3 |
HAVE | 0 |
HE | 20 |
HEALTH | 0 |
HEALTHCARE | 0 |
HELP | 0 |
HURT | 12 |
I | 84 |
IF | 0 |
I'M | 0 |
IN | 0 |
INCREASE | 16 |
INSURANCE | 0 |
INTO | 12 |
INVOLVED | 13 |
JUST | 13 |
KNOW | 13 |
LIKE | 12 |
LOT | 0 |
MAKE | 1 |
MANY | 0 |
ME | 5 |
MEDICARE | 16 |
MEDICINE | 11 |
MONEY | 14 |
MORE | 15 |
MUCH | 35 |
MY | 0 |
NEED | 0 |
NEEDS | 0 |
NO | 5 |
NOT | 44 |
NOW | 0 |
ON | 15 |
ONE | 20 |
OR | 1 |
OUR | 0 |
OUT | 0 |
PAY | 24 |
PAYING | 14 |
PEOPLE | 0 |
PROVIDE | 0 |
READ | 11 |
RIGHT | 0 |
SHOULD | 9 |
SO | 0 |
SOME | 0 |
SOMETHING | 0 |
START | 0 |
SYSTEM | 0 |
TAXES | 13 |
THAN | 0 |
THEIR | 9 |
THEM | 0 |
THERE | 0 |
THEY | 18 |
THINGS | 23 |
THINK | 68 |
THIS | 0 |
TOO | 48 |
UNINSURED | 0 |
UP | 4 |
US | 23 |
WANT | 35 |
WAY | 1 |
WE | 0 |
WELL | 14 |
WHAT | 21 |
WHEN | 0 |
WHO | 0 |
WILL | 34 |
WITH | 10 |
WITHOUT | 0 |
WORK | 33 |
WORLD | 0 |
WOULD | 6 |
YEARS | 0 |
YOU | 1 |
For data:
word | for diff |
---|---|
ABLE | 13 |
ABORTION | 0 |
ABOUT | 0 |
ACCESS | 12 |
AFFORD | 29 |
AFFORDABLE | 15 |
ALL | 0 |
ANY | 12 |
ANYTHING | 0 |
ARE | 44 |
AS | 2 |
AT | 2 |
BECAUSE | 69 |
BELIEVE | 0 |
BETTER | 30 |
BILL | 0 |
BUT | 1 |
BY | 0 |
CAN | 9 |
CAN'T | 15 |
CARE | 0 |
CHANGE | 14 |
CHILDREN | 12 |
COMPANIES | 24 |
CONTROL | 0 |
COST | 0 |
COSTS | 0 |
COUNTRY | 20 |
COVERAGE | 24 |
DO | 0 |
DOESN'T | 0 |
DONE | 0 |
DON'T | 0 |
ECONOMY | 0 |
EVEN | 13 |
EVERYBODY | 12 |
EVERYONE | 28 |
EXPENSIVE | 0 |
FOR | 0 |
FREE | 0 |
GET | 22 |
GO | 0 |
GOING | 0 |
GONNA | 0 |
GOOD | 0 |
GOVERNMENT | 0 |
HAS | 0 |
HAVE | 86 |
HE | 0 |
HEALTH | 17 |
HEALTHCARE | 107 |
HELP | 21 |
HURT | 0 |
I | 0 |
IF | 6 |
I'M | 4 |
IN | 12 |
INCREASE | 0 |
INSURANCE | 42 |
INTO | 0 |
INVOLVED | 0 |
JUST | 0 |
KNOW | 0 |
LIKE | 0 |
LOT | 28 |
MAKE | 0 |
MANY | 14 |
ME | 0 |
MEDICARE | 0 |
MEDICINE | 0 |
MONEY | 0 |
MORE | 0 |
MUCH | 0 |
MY | 6 |
NEED | 45 |
NEEDS | 11 |
NO | 0 |
NOT | 0 |
NOW | 9 |
ON | 0 |
ONE | 0 |
OR | 0 |
OUR | 4 |
OUT | 1 |
PAY | 0 |
PAYING | 0 |
PEOPLE | 104 |
PROVIDE | 11 |
READ | 0 |
RIGHT | 7 |
SHOULD | 0 |
SO | 27 |
SOME | 21 |
SOMETHING | 45 |
START | 12 |
SYSTEM | 10 |
TAXES | 0 |
THAN | 19 |
THEIR | 0 |
THEM | 14 |
THERE | 21 |
THEY | 0 |
THINGS | 0 |
THINK | 0 |
THIS | 13 |
TOO | 0 |
UNINSURED | 20 |
UP | 0 |
US | 0 |
WANT | 0 |
WAY | 0 |
WE | 40 |
WELL | 0 |
WHAT | 0 |
WHEN | 13 |
WHO | 20 |
WILL | 0 |
WITH | 0 |
WITHOUT | 13 |
WORK | 0 |
WORLD | 15 |
WOULD | 0 |
YEARS | 11 |
YOU | 0 |
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