#lab8

[bigmellyme]

[adamtcurrie]

Lab 8

http://ec2-54-148-30-123.us-west-2.compute.amazonaws.com/

Commits

https://github.com/adamcurrie/HTMLClock/commit/e384e5543e0d294e62a2f7a3cd42589e0f3a5ac5

https://github.com/adamcurrie/HTMLClock/commit/66273014f67bea9802ab69fc586701c76c2b65e1

https://github.com/adamcurrie/HTMLClock/commit/c8b2d176bbfd9d0ba7d48470c25504ac4bc29b31

[sunnie-goddess9474]

Microwave timer . #GotIt #Lab8 (at Southern California Institute of Technology)

[abhiarduino]

For this example I monitored the word "Justin Bieber" being mentioned on Twitter. For this I used twitter4j the Twitter Library for Java, and I used this particular tutorial to learn it. I used the same code I did for the Line Graph assignment, but this time I dynamically updated the count for each second, and put it into an array, which would reset every 1000s. So we could get a 1000 results before it would time out, and ran that in a huge while loop so every time the array reached 1000 it would just start back at 0. 

twitter4j was extremely easy to plugin and use in my processing code, and the code was short as well. Then I was able to use the Twitter API docs to pull in some requests for that keyword and pulled the count each time. So every-time a new request came through I would increment the count for that particular second by one, and then just ran the analysis that occurred and outputted the graph as shown in the video above.

The general process was as shown below, and I had global array for count and would just increment the count depending on the result.

Twitter myTwitter;

void setup() {

myTwitter = new Twitter("..", "..");

try {     Query query = new Query("Justin Bieber");     QueryResult result = myTwitter.search(query);  } catch (TwitterException te) {     println("Couldn't connect: " + te);     }; };

[abhiarduino]

For my line graph I got data from the Bureau of Labor Statistics of the U.S. I compared the Labor productivity (output per hour) via the Percent change from previous quarter at annual rate for Non-farm Businesses, and Businesses. The line going linearly downwards is for Non-farm businesses, as a oppose to the other one which is for Businesses. It's interesting because the x-axis the the year, and y-axis is the change in productivity in the major sectors. My data was generally just the values below, and they are per year and not per quarter.

Non-Farm Businesses

Farm Businesses

[abhiarduino]

Visualizing a single series of data

I did mine on the Tuition History at New York University. My source was CollegeCalc.org, which is a calculator for tuition and fees for individuals in the U.S.

My dataset is the following: 

$38765,$37372,$35290,$33420,$31690, $30094,$28496,$26646,$25380,$24336, $23456,$22586,$21730,$20756,$19748, $18739,$17640,$16650,$15620,$14502, $13336,$12250,$11130,$8714

Where it's going from 2010 to 1987. We can clearly see that there has been a positive rise. I manipulated some of the code I found on open-processing, and used it to create this particular bar graph.

[landdwellingursula-blog-blog]

[lolfunnywomen-blog]

LAB 8: A "3x3 GIF set":

Once again, my GIFing abilities apparently suck, so let's take a crack at this with the written word.

A critical concept of interest that I gained from the course readings and discussions in class was the importance of close reading. In other words, do not take things as they initially appear or say to be. This reminded me of the ole childhood saying, "Don't judge a book by its cover." Many of the course readings emphasized the importance to not dwell on initial perceptions and look at the discussed themes from a different angle. For example, Shimizu's "Hypersexual Filipina Video Ho" article was one of the more obvious portrayals of this concept. While initially expecting a rant from women about the hypersexualized portrayals of women in a Black Eyed Peas video entitled, "Bebot", the author took another view. Rather than saying the women were objectified, Shimizu pointed out many instances that the women were in fact empowered. She points out how the women are framed above men in many of the shots in the video, how they are in control in one way or another, etc. A closer look at the aesthetics of the video's images creates a whole new interpretation. Another example is Mayer's article, "Who Are Television's Producers?", in which the author dismisses the assumed title of television producer and divides it among several smaller, seemingly insignificant industry workers that equally contribute to the production of television. While people usually think of a television producer as one industry professional, Mayer skillfully points out television's many different producers. Lastly, in Deutscher's text, "Reading as Intervention", the author discusses the importance of deconstructive reading. Through the mentioned four different ways, Deutscher highlights the how deconstructive reading helps "gain a heightened awareness", "changes a text", "offers new ways of conceiving the onus of responsibility", and so on. Aside from the course readings, Prof. Miller would always encourage us in class to focus on particular details of concepts we discussed in class and analyze them within society as a whole. With an ever-changing media landscape, the importance of close reading is imperative to understanding these concepts' societal impact.