Here are the renderings Steve and I showed today, highlighting the initial views for our interface on a macro and (approaching) micro level:
Here’s the midterm from Ramsey and Aaron.
1. Overview
Our project explores the geographical locations that certain terms an associated with. The intention for this interactive visualization is to delineate the progression of different location’s significance, as they relate to specific terms. (i.e. what country was talked about most regarding “9/11″ between 2001-2003). We’re hoping that new narratives will arise from the proliferation of issues and news articles from the New York Times over the past 28 years.
2. Data
We’re still selecting our mapping API – but for now we’re intending to use:
3. Design Questions?
The main questions we’re asking thus far are:
4. Precedents
Our first precedent is a project from Yale called “Geographcially based Economci Data (G-Econ)”. This visualization shows economic fluctuations on a 3 diminutional geospatial model. This project is an example of how we might be easily convey the geographical significance of certain terms over a period of time.
The second precedent that we chose is Jer Thorp’s visualization entitled “Is Twitter the New Internet?”. This piece explores the usage of specific terms over time to show the proliferation of internet based services over the past 2 decades. We selected this piece because we’re also interested in term frequency within the New York Times article databases, but instead looking at the importance of locations within the context of specific issues.
5. Collaboration
We still haven’t worked out the specifics for this yet, but so far I will be working on most of the coding and Thai will be primarily handling the design for the project. These tasks will most likely overlap during certain areas of the project however.
I originally wanted to focus on how:
-People are on their cell phones a lot
-People leading busy lives having little time
-Information overload [amount of of new data generated in 2005 was many orders of magnitude
greater than the whole library of congress, several exabytes created, nearly 37,000 times more]
-How to make information fun
-Serendipity of finding interesting articles
I am still learning as3, so my first prototype is limited, only showing newswire headlines and
how long the article would take to read (iphone app in mind). I focused on the aspect of
time to read articles. For example, you might be waiting in a long line and only have time to
read a 5 minute article and not much more, even though there are more interesting articles to
read…time is of the essence these days.
prototype in as3
To address the bullet points above, I conceptualized a cross word puzzle that was created using
Aonaware dictionary API & Newswire NYT API. Answers to the crosswords are headlines from the last 24 hrs and
clues are taken from the dictionary API. Once any crossword item is found, a link to that article is made available on mouse hover. Words are color coded for Category [i.e. business, culture, etc.] and a number is posted on the last square to tell the user how long the item will take to read. This makes for a fun way to learn words, find serendipitous articles and make fun/efficient use of time.
Newswire crossword - data viz play
Told as a child that the NYTimes was more difficult to read and comprehend than other papers such as the Daily News and Newsday, I now seek to look for complexity within the NYTimes headlnes and then compare those findings against an analogous data set of headlines from more accessible newspapers to see if there is a divide between the NYTimes and it’s less respected brethren.
My data sets will be the NYTimes Newswire API + RSS feeds from papers both Local and National, including the USAToday Headline RSS.
A major question to tackle is hoe ease of read can be effectively mined from the data. I need to pay attention to studies on reading comprehension and search for indicators of reading sample difficulty. For now, I propose to assign longer headline length and higher range of word lengths within one headline to indicate higher difficulty.
I also need to consider mapping other data, perhaps newspaper section, time of day, or authorship in order to see if there are any other underlying relationships that can be connected to the varying reading levels across newspapers.
Previously, I explored the effectiveness of pie charts and am still interested in their use in effective data visualization, but am also interested in taking the feedback I received and implementing some sort of stacked bar chart visualization.
Dave Bowker’s project, Designing the News is a major work that deals with visualizing aspects of the Guardian newspaper in unconventional ways. In the project, Bowker produced a series of visualizations of the newspaper over the course of one week. Two of the resulting six pieces dealt directly with visualizing headlines:
http://www.designingthenews.com/wp-content/uploads/2008/04/06_saturday_a1_72.jpg
http://www.designingthenews.com/wp-content/uploads/2008/04/03_wednesday_a1_72.jpg
I am planning to partner with Rupa as she has similar interests in comparing the NYTimes headlines to headlines sourced from other places. So far we haven’t yet worked out how our collaboration will come together, but we’ll figure it out soon.
Midterm Project Proposal
Stephen Varga & Kunal D Patel
1. Overview
A short summary of what your project will be. Give me your best elevator pitch here.
Our project will be a real-time, split-screen image comparison of trending topic popularity on The New York Times and Twitter. Through analysis of comment activity and article keywords, we hope to generate a list of ‘trending topics’ to compare to Twitter’s well-established system. Both sets of keywords will be mined for relevant images using Bing’s recently announced API, with the images displayed in a side-by-side feed to serve as an immediate visual comparison of active topics amongst both environments. This visualization will compare and contrast popular subjects within a controlled environment in which users are provided content to discuss (NYT articles) versus an uncontrolled, user-generated environment (Twitter).
2. Data
The data sources you will be using
3. Design Questions
A set of questions that you intend to answer or explore. At least one question should be about the data itself (i.e., what is the story you’re hoping to tell?), but these questions may also address design methods or technical approaches.
4. Prior Art / Precedents
Discuss at least two existing works that are similar in some respect to your proposed project. How do you see your project in relation to this ecosystem of other works? Will it contribute something unique? Will it address problems that you see in other works?
10×10 – Jonathan Harris’ hourly scraping of several international news feeds, visualized as a sorted list of the 100 most “important” words in the news connected to a 10×10 grid of corresponding images.
Pingwire – Allan Grinshtein’s real-time visualization of images from 3 popular Twitter image-hosting services (twitpic, yfrog, and twitgoo).
In both of these works, the role of the user for each network is not readily addressed, which is where our focus lies. Harris uses his own algorithms for determining the 100 most important words in the news, and Pingwire is simply a real-time aggregated feed of hosted images. By approaching data mining and collection from the perspective of the users, we believe we are contributing a unique comparison of the cultures of The Times and Twitter.
5. Collaboration
A brief explanation of how you plan to collaborate with your partner.
For the purposes of data mining, the most effective solution will likely be to split the work between data sources. We both have experience with PHP and mySQL for mining and storing data, and the Bing API offers protocols we are both familiar with (JSON, XML). While we have yet to finalize a programming language for visualization, we will likely use openFrameworks for it’s speed and our familiarity with it. We will plan the visualization, data mining, context and interaction design processes together and split tasks as needed.
Here’s our pitch:
This visualization is a tag cloud of the newswire sections. The frequency of the section determines the weight in the cloud.
Parsing the sections to get the frequency was the toughest, but more rewarding part of working on this project.
I had some trouble adding urls for the tag cloud to the project, to make it more interactive. It’s something that I would want to add
in another iteration of the project.
Tag Cloud
I think of this as a widget that could be in the corner of a webpage.
The idea behind the initial design was to create a fun, interactive visualization which would encourage people to look at the news/headlines without the current restrictions of “sections.” The headlines self-organize into their sections eventually, but initially they roam the screen freely, allowing people to see connections between stories that might not end up associated with each other in the paper or on the site.
Code, images, and application
OK I’ve spent WAY too much time on this since class and I don’t really have a lot more to show than some interaction, so I’m calling it quits for now and here is the final project. Getting used to the New York Times API’s was fun and not too difficult, however creating visualizations in C++ is proving to be a very big challenge. I need to accomplish this for my thesis though so as painful as this was I really learned a lot and built a lot of things that I can use in the future to (hopefull) speed up the process significantly
The blog won’t let me embed vimeo video, so here are the screenshots and you can check out the video here
