RWET: Midterm

I like form. I find constraint to be an interesting mechanism for producing art, producing results we often could not have come up with consciously. That being said, the use of form has often directly related to ideas of personal expression and emotion, a way of structuring the subconscious or revealing an underlying architecture.

While thinking about poetic form, the relation between logic and nature I kept hitting on integer sequences in math. The most well known is the Fibonacci sequence, the one where the next number in the series is created from the previous two.

The Fib sequence is particularly revered because not only does it come up in lots of different mathematical explorations but in nature as well. Golden spirals/ratios are seen in seed patterns, leaf placement and even faces. It’s an example of the underlying logic of what may seem like random chaos.

I went through a lot of different ideas about what the source text could be, initially wanting to play with ideas of logic and emotion. But as I kept referring to Fibonacci as Gib I thought, what if it was specifically fibs, lies, that the program altered? A quippy play on words, fibbing fibbers and the fibs they tell…in fib sequence?

Some months back On The Media did a whole show about Political Lies. Politicians often get away with political lies because people don’t bother to fact check and then when they do, the first-impression, the lie, is still stronger than the truth. The lie is what people remember.

So I was curious about what kind of poetry could emerge using the Fibonacci sequence on some of the recent political speeches, as we are currently in the heat of the presidential primaries.

CODE, ATTEMPT 1:
I started by writing out my ideas for code in plain english

Screen Shot 2016-03-24 at 3.55.12 PM
I then realized that I should use lists, so I went back to the list code examples and played around with different examples that I thought would be helpful. After a few tries I came up with this code:

I showed the poems to my friend and it was pretty amazing how easy it was to guess the candidates from just a few words.

Ted Cruz, Remarks to the RedState Gathering in Atlanta, Georgia (August 8, 2015)
(from: http://www.presidency.ucsb.edu/ws/index.php?pid=114768)

Wow!
God
God
bless
RedState.
thank
that
unbelievably
Let
of
much
in
of
their
the
the
Supreme

Donald Trump, Remarks Announcing Candidacy for President in New York City (June 16, 2015)
http://www.presidency.ucsb.edu/ws/index.php?pid=110306

Trump:
Wow.
Wow.
Whoa.
That
some
people.
you
It’s
wonderful
like
big,
in
beating
from
of
now.
we
all
protect.
Member:

Bernie Sanders, Remarks Announcing Candidacy for President in Burlington, Vermont
(May 26, 2015)
http://www.presidency.ucsb.edu/ws/index.php?pid=110221

Thank
you
you
all
very
for
and
that
as
as
and
also
state
Super-PACs
change,
game,
median
us
senior

Clinton, Remarks in a Campaign “Kickoff” Speech in New York City (June 13, 2015)
http://www.presidency.ucsb.edu/ws/index.php?pid=110267

Thank
you!
you!
Oh,
thank
all!
so
is
you.
friends,
be
America,
the
America:
had
repairs…
powerful
politics.

I was slightly frustrated that for the sparseness of the text, many of the included words were “useless” or boring. I remembered that Nicole had a similar problem in an earlier assignment, which she solved through creating a list of “boring words” and if the code ran into one of these words to skip it. I asked Nicole if I could look at her code and went about adapting aspects to work with mine.

After running into some bugs (that in the end had little to do with that part of the code), I was able to get most of the “boring words” out. Except for the ones attached to punctuation.

Zach and I sat together and tried to use the .strip(‘”,.;:?!’) method that he had in his code. We ran into some issues of the possibilities of certain data types, like lists vs strings. With some moving around of different for loops we were eventually able to get rid of all the punctuation except for apostrophes and dashes. Offending words such as ‘that’s’ were added to the boring words text file to ensure they would not be present in the final text.

Here’s the code:

and a couple of examples.

**ok, my code started freezing up in terminal. I was able to parse one text, but after that the program keeps freezing. When I quit the program it says it’s having a problem with line 25, where the boring words are.

But honestly – looking at the following Cruz example using the same sample text as above:
Wow
God
God
bless
RedState
thank
extraordinary
you
conservative
you’re
Wow
you’re
you’re
Thank
consists
how
think
emailed

The lack of punctuation gives for a very different reading.
(Also I’m wondering if you’re should be on the boring list because 3 occurrences?!)

I decided to add back in exclamation and question marks to the punctuation and ran some more text, including op-eds in addition to speech transcripts.

Here’s one of Trump’s speech in Dallas,
https://www.facebook.com/MattWalshBlog/posts/1040241006009009

Wow
Amazing
Amazing
Amazing
thank
So
you
Teleprompters!
so
old
call
I
do
Dallas

And the Cruz speech is vastly improved from the last iteration, thanks to the return of exclamation marks:

Wow!
God
God
bless
RedState
thank
extraordinary
you
conservative
you’re
Wow!
you’re
you’re
Thank
consists
you
Wow!
We
home
bless

Or this one from Virginia,

Ted Cruz, Remarks Announcing Candidacy for President at Liberty University in Lynchburg, Virginia (March 23, 2015)
(from: http://www.presidency.ucsb.edu/ws/index.php?pid=109774)

Good
see
see
you
Good
you
you
you
you
see
Good
you
God
President
university
so
you
Italian
drank
children
She
pioneering

THOUGHTS:

In the end, the poems conform to the proposed form of using the Fibonacci sequence.

However,

I do with that they were visually stronger. Part of the reason I like the Fibonacci sequence is it’s exponential growth, seen in the Golden Spiral.

I tried to think through some ways that I could achieve this, but kept getting caught up in equating integers and words or strings (irregardless of Python types!). How does one add together words in somewhat sensical ways? Is it possible to parse a script when the numbers evolve exponentially so quickly that it’s difficult to equate to string characters or words?

Perhaps this is where the human hand could better come into play. Possibly it would be punching up the visual aspect. Zach and I joked about placing them in a spiral formation.

Also – why is it taking so long for the program to run in terminal?

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25. March 2016 by zoe.bachman.itp
Categories: RWET | Tags: , , , , | Leave a comment

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