DiggGraphr referenced in technical paper on news services using big data analytics

Quite a few years back, I got really interested in Treemaps. The whole project had started as an academic discussion between a friend and I on how hard a treemap would be to build (they seemed to be a pretty popular data visualization method back then, though I don’t see them around much these days). Anyway, what I thought would be trivial weekend hack turned out to be a lot more involved and I ended up reading and implementing Mark Bruls, Kees Huizing, and Jarke J. van Wijk’s algorithm for an optimum Squarified Treemap implementation (in ActionScript 3, you can find all the code which I open sourced here).

To demo the algorithm, I took the visual aesthetics of Marumushi’s NewsMap but instead used it to show trending topics on Digg.com. The project, not so creatively named DiggGraphr, got fairly popular and was mentioned on a few data visualization blogs and even won an award for a Digg.com API contest.

DiggGraphr has been dead for a while now, but I was pleasantly surprised to have it be included in a research paper titled ‘A case study on news services using big data analytics (뉴스빅데이터 서비스 사례 및 모델 개발 연구)’  conducted by professor Kim of the Korea Aerospace University and three researchers from a non-profit research organization (Media and Future Institute).

digggraphr.png

If anyone of you can read Korean, feel free to read the paper here

 

Author: Arpit Mathur

Arpit Mathur is a Principal Engineer at Comcast Labs where he is currently working on a variety of topics including Conversational Technologies, Affective Computing and Blockchains and decentralized services. Arpit has also worked extensively on Android and iOS applications, Virtual Reality apps as well as with web technologies like JavaScript, HTML and Ruby on Rails. He also spent a couple of years in the User Experience team as a Creative Technologist.

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