Final Proposal – Aaron and Ramsey

Presentation is here >

final project proposal

idea 1

Overview:

The story of the stars (working title) explores the mutual influence of pop music and news media. The intention of this interactive visualization is to find correlation between rise and fall and popularity of the musicians over time. This visualization will compare the musicians’ success or fail on billboard chart and social, personal events on news articles related to the musicians regardless of their reputation. ex, after Michael Jackson died, album sales goes up)

Data:

Billboard open API

To use names of the artists from the billboard chart

+

NYT article search API

To get frequency of the musician’s names from the article

+
sentimental analysis API(evri) + NYT community API

to see positive/ negative opinions from people’s comment

Precedent :

Twitter data viz from MTV VMA

Michael Jackson billboard chart timeline from NYT

idea 2

Overview
This project will visualize the change of ranking history  of bestselling books, and which publisher and author makes more/ less bestsellers, how long it takes for their books to become bestsellers after they are published( some books don’t get attention when they are published, but after certain events, suddenly they become top sellers. On the other hand, there are steady sellers. )

Data
NYT Best sellers api :
use ranking history, author, publisher, publish date

Precedents
360/365 Jer Thorp

idea 3

In the intrest of making data viz that can used in mobile platform, we thought about tracking hotspots in nyc ara. this idea is kind of broad as well, but might be worth exploring further. using nyt real estate api and other source like twitter( some place people casually talk about things ), how some area is more popular( sold well, get more attention) than others, which can be used as a tool to predict future rise in real estate market.

so with mobile phone, the visual will be changed based on the user’s location and the popularity of the spot.

out of sight, out of mind

1. Overview
My project will map the frequency of words related to the wars in Afghanistan and Iraq in relation to the number of American casualties in those two conflicts.

2. Data
NY Times Article Search API, TimesTags API, http://icasualties.org/

3. Design Questions

The shape of a graph of casualties in Iraq and Afghanistan will obviously be one that increases over time – sharply at first, then more slowly as time passes. My question is how much and until what point the number of
articles regarding the wars in the two regions follows the same slope. I would probably track these numbers month by month. I would also like to compare Iraqi civilian casualties, but this will be much more difficult. It would also be interesting to see the first mentions of an insurgency, as well as terms relating to withdrawal from the conflict.

4. Prior Art / Precedents

Most of the data visualizations I’ve seen about the war in Iraq have  plotted the casualty count data against date, where the deaths took place, where the soldiers were from, and how their number compared to estimated Iraqi civilian deaths. I have not seen any that address the coverage of the conflict in the media or how it changed over time. I feel that this pattern makes the stories told by other data visualizations about the war that much more powerful and moving.

*Edit: Lie by Lie is an amazing interactive timeline of the events leading to the war in Iraq and asks who knew what when: our leaders, journalists, commentators, etc.

TweetCatcha Proposal [Final]

>> Presentation <<

Tweetcatcha

Here is what Bruce and I presented in class today, the tweets are not loading online for some reason, but the basic functionality is there.

This prototype is for functionality purposes only. We are moving towards this aesthetics once we achieve the functionality that we desire.

[Final] NYT Article Polarity Visualizer Proposal

Since Steve and I began with a different proposal, I’ll recap what we’ve done and where we’re heading:

Final 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 focuses on the polarity of comments on the New York Times website as a means of tracking public opinion about articles and topics. Through a robust time-based interface, we are interested in seeing the potential ebbs and flows of commenting, if we can spot “influencers” that shift polarity, and explore the topics generating the most positive and negative discussion.

2. Data
The data sources you will be using

• The Community API – we’re making a call 1x a day to pull all of the previous day’s comments and store them in a SQL database
• The Article Search API – after grabbing all the comments for the previous day, we store the articles they correspond to into a separate table in the same database
• Amplify API – we’ve now been granted access to the client services for Amplify, a sentiment engine that we are using to parse through the comments

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.

• Does the polarity of an article (how positive or negative it is) substantially influence the polarity of its comments?
• Do comments for an article tend to fall within a narrow range, or is there often variation?
• Through a time-based visualization, will be able to identify “influential” comments that (qualitatively) appear to shift comment polarity?
• Will Amplify be able to conduct meaningful and consistent topic extraction and sentiment analysis?
• Do we have enough time to develop a robust enough interface components to support comment AND topic searches?

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. These words are generated by his own algorithms from the articles themselves. Our focus is on comments to see what the NYT community feel are the most important and polarizing topics for discussion.

Twittermood – Twittermood conducts basic sentiment analysis on tweets using the ANEW dataset (which assigns emotional values to words) and maps the results in real-time. Besides the difference in audience, our planned interface is far more robust, allowing for navigation by week, day, author, and article in order to view patterns.

5. Collaboration
A brief explanation of how you plan to collaborate with your partner.

Steve and I worked together to write the PHP scripts to parse through the NYT API’s, pull the relevant data, and store it into a SQL database running on Steve’s web server. I’ve been focusing on working with the Amplify API and developing interface wireframes while Steve’s attention has been devoted to developing a working prototype in openFrameworks. For the rest of the semester, we will retain our individual foci in order to efficiently divide tasks, but our work will converge much more as the interface takes shape.

Congress Tweets

Our project, CongressTweets, looks at the relationship between your Congressmen’s political activity in Congress vs his/her activity on twitter. We are trying to find out if twitter activity is a good measure of political activity and good way for communicating with constituents. We were also interested in looking at voting trends relating to party, gender, and geography.

For this project we used the NYTimes Congress API as well as several Twitter related APIs.

Please find a zip of our code here

Opening Page

Missed Votes % vs Voted with Party % (Representatives)

Missed Votes % vs Voted with Party % (Senators)

Someone tweets a lot!

So does this guy!

Congrats, You Can Read the New York Times

Midterm Project by Rupa & Bobby.

This project started with a curiosity stemming from the standardized English Language Arts tests taken by all elementary school children in the NYCity public school system. When I was in 3rd grade, the highest percentile of test takers were told that they had a level of reading comprehension that enabled them to read the NYTimes. This experience led to questions:

1. how is reading level measured
2. are nytimes articles truly challenging
3. how does the NYTimes compare to other news publications with comparatively lower reputations
4. how might such a  comparison be visualized

Research indicated that many methods to calculate reading level exist and that most rely upon counting syllables (due to the complexity of polysyllabic words).  Our tests showed that the NYTimes is consistently more difficult to read than Newsday, USA Today, the Wall Street Journal, and the Washington Post.

Interaction between stock market price and news article of New York Times

Interaction between stock market price and news article of New York Times
by Yoon and Seung

Detail description, screen shots and Demo page Link

Presentation PDF

- Currently company stock prices are not normalized (Can go out of the screen)
- Full screen is supported (Right click – ‘Go Full Screen’)

[Midterm] NYT Article Polarity Visualizer

Here are the renderings Steve and I showed today, highlighting the initial views for our interface on a macro and (approaching) micro level: