Python

Wisdom of the Crowd: People Are Lonely, for Being Lone

May 6, 2014 by michellechandra in Python

For my final for Reading and Writing Electronic Text, I am exploring using the “wisdom of the crowd” to answer a simple question: What is the experience of loneliness?

The idea of answering a question using the “wisdom of the crowd” is derived from an experiment by Sir Francis Galton in 1907, when he asked 787 villagers to guess the weight of an ox. Individual responses varied wildly, but the average of all these responses was within one pound of the real weight of the ox. The wisdom of the crowd uses the collective opinion of a group of individuals to answer a question. Modern day examples include Wikipedia and Google.

I collected from the internet ~100 quotes on the experience of loneliness from well-known people throughout history. I wrote a program in Python to mashup the wisdom quotes by combining portions of each quote together to create new quotes, in effect sampling from my loneliness canon. I took my mashed-up quotes, and used character markov-chain analysis to generate new text that is statistically similar to the original quotes. I ran my statistically generated text through the markov-chain analysis 1-3 times, just to make sure my text was nicely average.

So, according to the wisdom of the crowd, what is the experience of loneliness?

People are Lonely, for Being Lone
Loneliness can be conquered only by Lonely people
If you’re lonely than There is a loneliness
Loneliness is more lonely
People are lonely when you’re alone

I used this generative collective wisdom to create a poem, three stanzas in length, to help distill the wisdom of the crowd on the topic of loneliness. Many thanks to the intellects whose wisdom I stole to inform this new poetic form: → Read more

ITP ListServ Network Visualization

April 12, 2014 by michellechandra in Data Visualization, Processing, Python

ITP is a two year graduate program at NYU focused on the intersection of art and technology, “a Center for the Recently Possible.” One way a sense of community and connection is facilitated is with the ITP student listserv, host to all sorts of email conversations between students on everything from missing power chargers to animated gifs and pop culture.

My experience of the ITP student listserv upon arriving at ITP in the Fall of 2013 was one of mostly confusion, my inbox suddenly overwhelmed by a barrage of emails from people I didn’t know replete with animated gifs and insider jokes. By the Spring Semester of this year, my sense of the listserv was that it seemed largely dominated by Second Year students, who seemed to mainly just be speaking with Second Year students with minimal participation by First Year students.

I decided to test my theory by gathering my gmail data and creating a network visualization of the ITP listserv.

First Year students are grouped on the right hand side of the circle, and Second Year students on the left side. The density of lines is much greater on the left side of the circle, indicating there are more public conversations taking place between Second Year students.

During the process of researching for this project, I discovered an ITP student listserv network visualization made in 2007 by Joshua Knowles. My visualization chooses as its reference point the 2007 visualization, but I have many ideas to expand on this earlier visualization including making the visualization interactive so users can more deeply explore the data, and visually exploring the class imbalance of listserv usage.

I believe it is important to explore data in context. Once my data visualization is interactive, I would like to user-test it with ITP students, while also getting feedback from students on their own individual experience of the listserv and the ways it could be improved upon.

So how did I create this visualization? With Dan Shiffman’s guidance, I wrote a Processing program to visualize the ITP ListServ:
→ Read more

Functions and Python

April 10, 2014 by michellechandra in Python

For this week’s homework in Reading and Writing Electronic Text, I took two Python programs and rewrote the programs to be functions. Here is the revised sketch for my Corporate Motto mashup program:


import sys
import random

def get_words_from_file(filename)
    file1_lines = list()
	for line in open(filename):
		line = line.strip()
		file1_lines.append(line)
	return file1_lines

words_from_file = get_words_from_file("corporatemotto2.txt")

def create_slogan(words_from_file)

slogan_a = random.choice(words_from_file)
slogan_b = random.choice(words_from_file)

slogan_a_words = slogan_a.split(" ")
slogan_b_words = slogan_b.split(" ")

first_part = " ".join(slogan_a_words[:4])
second_part = " ".join(slogan_b_words[2:])

return first_part + " " + second_part

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import sys

import random

def get_words_from_file(filename)

file1_lines = list()

for line in open(filename):

line = line.strip()

file1_lines.append(line)

return file1_lines

words_from_file = get_words_from_file("corporatemotto2.txt")

def create_slogan(words_from_file)

slogan_a = random.choice(words_from_file)

slogan_b = random.choice(words_from_file)

slogan_a_words = slogan_a.split(" ")

slogan_b_words = slogan_b.split(" ")

first_part = " ".join(slogan_a_words[:4])

second_part = " ".join(slogan_b_words[2:])

return first_part + " " + second_part

→ Read more

Propaganda Poetry

March 27, 2014 by michellechandra in Python

It’s time to write a program to make a poem! I decided to make propaganda poetry for Reading and Writing Electronic Text. Hopefully very bad propaganda poetry.

I dug up some books from the library and compiled a text file with war slogans from World War Two posters (British and American.) I also created a text file with headlines from The Economist (always mysteriously poetic!) and threw in my corporate mottos to the mix for good measure.

I think the results are actually pretty good for being fairly nonsensical. Here are my favorite poems that were generated. (You can find the code for the program at the end of this post.)

Poem One
Relearning old lessons
we trust
All that glitters is
kill

This is the enemy.

Keep that lumber coming!
Is your trip necessary?
Grow vitamins at your kitchen door.

Just a good afternoon’s
Bad ventilation ruins ammunition.

Poem Two
Buy victory bonds. Invest.
Come into the factories.
United we are strong.
Do it! Keep ‘em firing!

The daily diary of
neighbor, State Farm is there

A few careless words
If you are bombed

→ Read more

ITP ListServ Visualization: Getting My Gmail Data Using Python Gmail Library

March 18, 2014 by michellechandra in Data Visualization, Python

Today I figured out how to use this Gmail Python Library to fetch Gmail data for my ITP listserv visualization. First up, I installed the Gmail Python library by cloning the GitHub repo to a folder on my local computer.


git clone git://github.com/charlierguo/gmail.git

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git clone git://github.com/charlierguo/gmail.git

In Terminal, I changed directories so I was in the directory where I saved the library.


cd /Users/michellechandra/rwet/gmail

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cd /Users/michellechandra/rwet/gmail

I then installed the GMail Python library:


python setup.py

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python setup.py

And opened the Python Interpreter in Terminal:


python

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python

and ran these commands to log-in to my Gmail Account:


import gmail

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import gmail


g = gmail.login('username'. 'password')

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g = gmail.login('username'. 'password')

This command accesses messages labeled “ITP” in my Inbox: → Read more

Data Representation: ITP ListServ Visualization

March 18, 2014 by michellechandra in Data Visualization, Python

I am tackling what at times feels like a herculean Data Representation project, although on paper it sounds easy: visualize the connections between folks who use the ITP student listserv. In 2007, Joshua Knowles did just that.

This post is about how to not tackle this project.

For my first attempt at getting my gmail data, I ran this Python script and downloaded 6,126 emails (as separate text files) sent to the ITP listserv from Sept 5, 2013-Present. Luckily, Gmail has been archiving these emails for me in a separate folder in my Inbox (plus one for me!) I then attempted to adapt one of Dan O’Sullivan’s Gmail Word Count Processing sketches in order to loop through each text file, grab the From and Subject line and write to a CSV file. This turns out to be exactly the kind of sketch that crashes Processing. It’s just too much data for Processing + my computer to manage given I do not need each email (and all of that data including attachments) for this project. → Read more

Python: Corporate Motto Mashups Part Deux

March 6, 2014 by michellechandra in Python

For my second pass at my Corporate Motto mashups, I recombined mottos by splitting each motto based on a certain number of words and recombining the mottos into a new motto.


import sys
import random

stuff = list()

for line in sys.stdin:
	line = line.strip()
	stuff.append(line)

slogan_a = random.choice(stuff)
slogan_b = random.choice(stuff)
slogan_c = random.choice(stuff)

#print slogan_a[:10] + slogan_b[10:]

slogan_a_words = slogan_a.split(" ")
slogan_b_words = slogan_b.split(" ")
slogan_c_words = slogan_c.split(" ")

first_part = " ".join(slogan_a_words[:4])
second_part = " ".join(slogan_b_words[3:])
third_part = " ".join(slogan_c_words[5:])

print first_part + " " + second_part + "." + " " + third_part

#print first_part + " " + second_part

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import sys

import random

stuff = list()

for line in sys.stdin:

line = line.strip()

stuff.append(line)

slogan_a = random.choice(stuff)

slogan_b = random.choice(stuff)

slogan_c = random.choice(stuff)

#print slogan_a[:10] + slogan_b[10:]

slogan_a_words = slogan_a.split(" ")

slogan_b_words = slogan_b.split(" ")

slogan_c_words = slogan_c.split(" ")

first_part = " ".join(slogan_a_words[:4])

second_part = " ".join(slogan_b_words[3:])

third_part = " ".join(slogan_c_words[5:])

print first_part + " " + second_part + "." + " " + third_part

#print first_part + " " + second_part

The first round of mashups returned some funny results, but mainly mottos that almost sounded like they could be real mottos. Some of my favorite ones:

Even your best friends won’t tell you!
Snap! Crackle! Pop! just one!
You’ve come a long way, baby.
We Help You life.
It looks good, it cleans your teeth.

I then took the first results, and passed them back into my corporate motto program. Round two returned much more ridiculous mashups: → Read more

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