Jeremy Diamond


InArticle is a web-based exploratory tool for gathering related articles, analyzing their content, and visualizing it in an easily comparable format.

One of my main inspirations is Mitchell Whitelaw, a digital artist, designer, data visualizer, and lead of the Master of Digital Design program at University of Canberra. Most of his recent work has been with what he calls "generous interfaces" for large collections or archives. These projects include the Flickr commonsExplorer, and the Visible Archive (which visualises the collection of the National Archives of Australia). What I take from Mitchell's work is a sense of exploration. He creates tools for exposing a world of material that are easy to use, offer content in helpful ways, and encourage digging around.

Jer Thorp's visualization of the top organizations and people mentioned in articles in The New York Times over the course of a year. Jer shows the importance and connections between the huge amount of content the New York Times creates, exposing themes that represent the period. And it's pretty!

Understanding Shakespeare, by  Stephan Thiel. For his thesis project, Stephan created a set of computational tools to extract and visualize the information found within Shakespeare's plays. He made five approaches to the text analysis, each highlighting different aspects to reveal "underlying narrative algorithms".

Two different projects on visualizing the insertions and deletions of text through six editions of Darwin's Origin of Species. Two very different approches:
1. Ben Fry & Fathom: This an amazing interactive java app that shows a time-lapse of the edits and exposes portions of the text. This was my main inspiration for the article layout in my project.
2. Stefanie Posavec & Greg McInerny: This is simply an aesthetic pleasure. Not as informative as the Fathom version, but certainly more pretty.

Implementation is a web-based exploratory tool for gathering related articles, analyzing their content, and visualizing it in an easily comparable format. Using the GoogleNews breaking stories feed, InArticle collects the most prevalent links for related articles, scrapes their text, and parses it for key items such as named entities (people, places, organizations), quotations, n-grams (common phrases),  and sentiment. This data is then used to create an interactive “text map” of each article as well as a “relation chart” that displays the levels of connectivity amongst them. The “relation chart” provides a simple, graphical way of summarizing the articles' key content, to see where information is consistent or divergent. In addition to the automatic news feed, InArticle allows you to submit your own links to articles for comparative visualization.