This visualization shows how NY Times articles travel through Twitter after being published. It visualizes the tweets resulting from the latest news articles that appeared during the bygone 24 hours on the New York Times website.
Tweetcatcha uses the New York Times Timeswire API to load the latest news. The API is used to get links and metadata for Times articles as they are published on NYTimes.com. The BackTweets API then searches for the relevant tweets using the title and URL of those articles.
Articles are arranged in a circular manner and each article is represented in the form of a small clickable bar, which shows the total tweets pertaining to that article and a little description about it. There is an option for reading more about that article which takes you to the actual link of the news. The other option, “Zoom In” takes you to a page, which has 24 rings indicating an hour difference from the first ring till the last one. On or between each ring there is a small cloud, which on clicking pops up a small box showing a tweet. The position of tweets is based on the time difference between when the article was published and when it was tweeted.
The data for this visualization was collected from November 13, 2009 until February 9, 2010. This visualization uses a database of 107 MB with 15, 327 NYTimes articles and 311,885 tweets related to those articles.
The visualization is useful to people who are interested in the popularity of a particular news (which is shown by the number of tweets tweeted). It makes understanding the timing and density of tweets pretty easy. It also shows within 24 hour which news was most popular. It interests people who are active in social media and how it grows. It becomes easy for them to track the trends and behaviours.
Link to the example: http://a.parsons.edu/~drumb588/tweetcatcha
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