For the Javascript node exercise I decided to pull from two essays I wrote last year. One of them was an essay on self-reflection in fencing and the other essay was from my advanced standing proposal. As James Pennebaker mentioned in his TED talk, if we are writing to those who are above us, we’ll tend to use I more. Though both were mostly self-centered I wanted to see how much I used I before certain words in both essays. I decided to pull out how much I used ‘I’ and ‘my’ in both of these essays. ‘My’ showed up 13 times and ‘I’ showed up 24 times. ‘My’ was mainly followed by words in regards to my art, while ‘I’ came up mostly when I discussed what I was intending to do. In the fencing essay ‘I’ showed up 94 times and my showed up 46 times. ‘I’ came up when discussing what I did when describing those moments and when I was writing about ways I could improve. ‘My’ came up when reflecting on what fencing meant to me as a fencer and what it meant to me in my daily life.
I think both of these essays are good representations of how common self-reflection words are used when trying to discuss one’s own current situation and looking ahead at the future. I see it the most when I’m discussing parts of who I am and what makes me who I am.

My goal for this assignment is to make a practical twitter bot. More specifically, a bot that people can use to help themselves/ their companies. I emailed a boss of mine at ClickOn asking how I might be able to use a bot to help the company, she responded saying (basically):

Is there a way to find out who our most influential followers are?

Is there way to find out who the most influential Golf or Pet Twitter accounts are?

We could really benefit from anything that assists us in learning more about our audience & desired audiences.

My friend that works at Droga 5 says they have a system specifically designed for Twitter that they can use to find out what their core audience is talking about. That could be something interesting to look into as well. Very valuable tool. We are always trying to find out what is on people’s minds but it is tricky when you are only shown 5 or so trending topics in the side bar.

Basic Bot Ideas:

“GossipBot” – posts based on reactions of others

“NotSoTrendingBot” – tweet topics that aren’t currently trending, artistic stance or maybe practical in hopes of getting new topics trending

“InfluenceBot” – Who are my biggest inspirations/influences? Who do I tweet the most/ who tweets at me the most?

“Trendbot” – Tweet about all trending topics + some more than the basic 5 suggestions

“Practibot” – Get real/practical data about a group of people/audience. What is being talked about, why, to whom are they talking…etc.

The Anxieties of Big Data, Kate Crawford

Art, Activism, and CCTV

The Anxieties of Big Data by Kate Crawford discusses the ways in which big data collection affect users on an every day social context.  In recent years, the public has started to become more aware of their thinning privacy and increasing surveillance by the United States government. Much of this surveillance has been defended as being in place for the safety of the general public, especially in a post September 11th with the fear of terrorism being a main threat.  In 2013, Edward Snowden, a former employee of the National Security Agency (NSA) came forward leaking documents to the media stating that would show the United States government was performing illegal and unethical surveillance on other countries and it’s own citizens.

The Anxieties of Big Data discusses the type of society that is evolving as a result of big data collection.

Interestingly, Crawford mentions that the reality of big data is surveillant anxiety.  She defines this term as “the fear that all the data we are shedding every day is too revealing of our intimate selves, but may also misrepresent us.”

Crawford also references Plan C’s manifesto, “We Are All Very Anxious”, to address a significant problem society faces today, arguing that anxiety is the affect of our current structure of capitalism that is the causation of political apathy, insecurity, and social segregation.

Crawford also argues that anxiety comes in two places – the anxiety of the surveilled and the anxiety of the surveillers.  This is a crucial catch 22 in the surveillance divide.  The general public is told their safety is at risk which enables the surveillance, but the surveillers become increasingly skeptical of the public.  Then, as Crawford describes, the actions of those exercising control of data collection are hidden by government documents that the public does not have access to.  As their actions remain hidden, the public becomes defenseless as to what is being done with their information and remains blind to any real intentions.

Many people have accepted data collection as an increasing part of every day life.  The question that has been apparent however, especially since Snowdens leak of government documents, is how much this data collection really benefits the public.  Crawford describes the “current mythology” of big data as being more data = more accuracy, more truth.  Many argue however that this just isn’t true, and correlation doesn’t imply causation.  Many worry, understandably so, that big data leaves too large a chance of misunderstanding.

Crawford expands her argument to everyday trends and fashion.  She uses the current style of “Normcore” as an explanation of consumer anxiety and being a reaction to surveillance.  Normcore addresses how blending in was once a tactic used by protestors (ex. Occupy Wallstreet) to avoid police detection and surveillance.  As big data collection increases however, blending in is now more important than ever, and everyone must partake.

Art, Activism, and CCTV

Dead Drops- Adam Barthol – art project that involves exchanging files through USB devices in public places

“Creativity generates tactics. Art can be a weapon. It is valuable enough to society that forces of power have worked to subvert it.”

System Azure- Jill Magid –

What’s interesting to point out here is the way the perception changes when someone approaches a situation as an artist versus other jobs titled “professional.”

Discussion Questions:

1. Do you think your privacy is a fair trade off for the feeling of safety?

2. Do you think someones online data is an accurate representation of them as a person? Could they be misconstrued?

3. Do you think every day users have any control over the future of big data collection?

4. In what ways do you think data collection has benefitted your safety and/or general well being and happiness?  In what ways has it inhibited?

5. What anxieties do you think surveillers experience versus the anxieties that those being surveilled?

6. Why do you think the police rejected her proposal after finding out she was an artist? What is the power in being an artist in these situation

“An Entomologists Last Love Letter”

Every Other Word:

I used one of my favorite poems Slowdance by Matthew Dickman.

I thought this exercise was really amazing to see how it can transform text in an interesting way and how it changes language.  Really liked this exercise.

First, I used the every other example code.Here was the result:

gungho:SSHW emilylocke$ node everyother.js text.txt

More putting man the

more a Year’s of and

we the to

with exquisite A dance the and room at end the while person love gone bring car

because begun rain would their

if part us wet. slow

to the home, knock out the Two

rocking and like buoy. extravagant. little An bottle whiskey. a like Your resting his your moving his

Your along spine. hips like cotton

and begin think how the in sky dead. my

is to body dance. Unchained

Stairway Heaven, slow All life made Small cruel. made plans. never I my I my

The dance care. all like

before turn Like held the

of brother. slow of

Two in middle the When dance him, of great he absolutely

and he to me I on foot we both

I that of will first the will

The dance what’s come the dance insomnia across floor bath

When woman sleeping

stands in bathroom, her the dance ritual being

into sink. is one save

because is need be

I’ve you. loved I’ve

the yard. the wearing shear dress in million

comes me an chandelier come life, take hand mine. spin out bring in. is almond

in dark dance. is we be right Scrapping joy. haiku honey. orange orangutang dance.

Then I tried reversing: 

gungho:SSHW emilylocke$ node reverse.js text.txt

.ecnad wols gnatugnaro dna egnaro ehT .yenoh dna ukiah ehT .yoj rof

gnipparcS .won thgir gniod eb dluohs ew tahw si tI

.ecnad wols krad eht ni

evorg dnomla eht si sihT .ni reh gnirb dna

tuo reh nips I .enim ni dnah reh ekat I

,efil ot emoc ylneddus reilednahc dexes-revo na ekil em drawot semoc

sdaeb noillim a ni derevoc

sserd etihw raehs a gniraew regnarts eht nehW .dray tnorf eht

dewom ev’I .uoy devol ev’I .uoy truh ev’I

.devas eb ot deen on si ereht esuaceb

su evas ot eno on si erehT .knis eht otni

tips gnieb si lautir fo ecnad wols eht ,hteet reh gnihsurb

,moorhtab eht ni dekan sdnats

htiw gnipeels m’I namow eht nehW

.retaw htab ekil roolf eht ssorca gniruop

ainmosni fo ecnad wols eht dna

emoc ot s’tahw fo ecnad wols ehT

.reffus lliw rehto eht dna tsrif eid lliw su fo eno taht wonk I

,gnidael htob era ew esuaceb toof sih no pets I ro

em pid ot snrut eh nehw dna

,namuh yletulosba si eh ,sevol taerg ym fo eno

,mih htiw ecnad I nehW .moor eht fo elddim eht ni nem owT

.sgnilbis fo ecnad wols ehT .rehtorb ym fo

smra eht ni dleh gnieb ekiL .ruof nrut yeht erofeb

nerdlihc ekil ssendnik lla s’tI .erac t’nseod ecnad wols ehT

.eniw ym knard I .doof ym eta I .devirra reven I

.snalp ym edam I .leurc dna

llamS .sekatsim edam ev’I

efil ym llA .ecnad wols droc-rewop ,nevaeH ot yawriatS

,ydoleM deniahcnU ehT .ecnad wols ydob ruoy ot gniklat si

ydob ym ehT .daed era

yks eht ni srats eht lla woh tuoba kniht ot nigeb uoy dna

nikpan nottoc a ekil gnidlofnu

spih reH .enips reh gnola sdnah ruoY

.kcen sih pu gnivom htaerb ruoy ,redluohs sih no

gnitser daeh ruoY .gnitaehc ekil elttil a s’tI

.yeksihw fo elttob ytpme nA .cisum elttil A

.tnagavartxe gnihtoN .youb a ekil htrof dna kcab gnikcor

elpoep owT .krap eht fo tuo ti kconk ot ,emoh gnineve eht gnirb ot

ecnad wols A .tew tog su fo trap yna fi

traeh rieht kaerb dluow dna niar ot nugeb s’ti esuaceb

dnuora rac eht gnirb ot

enog sah evol ew nosrep eht elihw ,ytrap eht fo

dne eht ta ,elbat moor gninnid dna hcuoc eht neewteb

ecnad wols A .sregnarts etisiuqxe yllaer htiw

ecnad ot ytinutroppo eht deen ew

,agoy dna trugoy fo noituloser s’raeY weN a naht erom

,noom eht no nam rehtona gnittup naht eroM

Here is Flesch:

gungho:SSHW emilylocke$ node flesch.js text.txt

Total Syllables: 534

Total Words    : 418

Total Sentences: 39

Flesch Index   : 87.87877008955958

————EVERY OTHER WORD ————

The Raven – Edgar Allan Poe

Once a dreary, I weak weary,
Over a and volume forgotten –
While nodded, napping, there a of one rapping, at chamber –
“‘Tis visitor,” muttered, at chamber –
Only and more.”

Ah, I it in bleak each dying wrought ghost the I the – I sought borrow
From books of – for lost –
For rare radiant whom angels Lenore here evermore.

And silken, uncertain of purple me filled with terrors felt that to the of heart, stood some entreating at chamber –
Some visitor entrance my door; it and more.”

Presently soul stronger; then longer,
“Sir,” I, Madam, your I the is was and gently came so you tapping, at chamber I was I you” here opened the –
Darkness and more.

Deep that peering, I there fearing,
Doubting, dreams mortal dared dream the was and stillness no the word spoken the word, I and echo back word, –
Merely and more.

Back the turning, my within burning,
Soon I a somewhat than said “surely is at window me then, thereat and mystery –
Let heart still moment this explore; the and more!”

Open I the when, many flirt flutter,
In stepped stately of saintly of the obeisance he; a stopped stayed with of or perched my door upon bust Pallas above chamber –
Perched, sat, nothing this bird my fancy smiling,
By grave stern of countenance wore,
“Though crest shorn shaven, I “art no grim ancient wandering the shore me thy name on Night’s shore!”
Quoth Raven I this fowl hear so its little – relevancy we help that living being
Ever was with bird his door or upon sculptured above chamber such as the sitting on placid spoke one as his in one he outpour.
Nothing then uttered not feather he –
Till scarcely than “Other have before the he leave as hopes flown the said at stillness by so spoken,
“Doubtless,” I, it is only and from unhappy whom Disaster
Followed and faster his one bore the of Hope melancholy bore
Of – the still my fancy smiling,
Straight wheeled cushioned in of and and upon velvet I myself linking
Fancy fancy, what ominous of –
What grim, ghastly, and bird yore
Meant croaking I engaged guessing, no expressing
To fowl fiery now into bosom’s and I divining, my at reclining
On cushion’s lining the gloated whose violet with lamp-light o’er,
She press, nevermore!

Then, the grew perfumed an censer
Swung Seraphim foot-falls on tufted I “thy hath thee by angels hath thee
Respite respite nepenthe, thy of oh this nepenthe forget lost the “Nevermore.”

“Prophet!” I, of – still, bird devil! Tempter or tempest thee ashore,
Desolate all on desert enchanted this by haunted tell truly, implore there is balm Gilead? tell – me, implore!”
Quoth Raven said “thing evil prophet if or that that above – that we adore this with laden within distant shall a maiden the name –
Clasp rare radiant whom angels Lenore.”
Quoth Raven that our in bird fiend!” shrieked, –
“Get back the and Night’s shore!
Leave black as token that thy hath my unbroken! quit bust my thy from my and thy from my the “Nevermore.”

And Raven, flitting, is still sitting
On pallid of just my door;
And eyes all seeming a that dreaming,
And lamp-light him throws shadow the my from that that floating the be –

————FLESCH INDEX————

Andrews-MacBook-Pro-3:SSHW MrPC$ node flesch.js raven.txt
Total Syllables: 1560
Total Words    : 1072
Total Sentences: 61
Flesch Index   : 65.88568265231221

————SEARCH————
This is case sensitive!

Andrews-MacBook-Pro-3:SSHW MrPC$ node search.js raven.txt raven
Andrews-MacBook-Pro-3:SSHW MrPC$ node search.js raven.txt Raven
Raven of
1
Raven wandering
2
Raven “Nevermore.”

Much
3
Raven still
4
Raven “Nevermore.”

“Prophet!”
5
Raven “Nevermore.”

“Prophet!”
6
Raven “Nevermore.”

“Be
7
Raven “Nevermore.”

And
8

Findings:

For this assignment, I chose to analyze Edgar Allan Poe’s “The Raven”. I chose this poem because I was curious to see how the language/writing would look when analyzed and manipulated. I ran the text through the “everyother”, “flesch”, and “search” scripts.

The “every other ” program produced interesting results, an entirely new poem! The interesting thing is, since the chosen text is not pros any form of manipulation could be considered art! So after the txt was manipulated, a whole new work was produced and at points comical.

The next piece of code was the flesch test. This test produced results that you would expect… nothing out of the ordinary there.

Finally the search script, searching for the word Raven. The important thing to note here was that the search word is case sensitive! (talked about in class ‘God vs god’)

I’d be interested to take some of the code examples and modify them to produce more interesting results. I’d like to change the “every other” code to maybe have several functions within that are chosen randomly upon running. Maybe one to give you every other word, one to give you words on either side of periods, etc… you could run text through the program and create poems or interesting works of art. I thought this was interesting and fun, as well as potentially very useful.