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A Data Analysis of iTunes’ Top Charts Algorithm. Jan 20, 2015 0 comments. A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com. Here’s the overview:. Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose. If these volatile days are deliberate, shouldn’t we be informed? These are people who pour coun...

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A Data Analysis of iTunes’ Top Charts Algorithm. Jan 20, 2015 0 comments. A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com. Here’s the overview:. Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose. If these volatile days are deliberate, shouldn’t we be informed? These are people who pour coun...

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dataworks | data musings at betaworks | data.betaworks.com Reviews

https://data.betaworks.com

A Data Analysis of iTunes’ Top Charts Algorithm. Jan 20, 2015 0 comments. A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com. Here’s the overview:. Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose. If these volatile days are deliberate, shouldn’t we be informed? These are people who pour coun...

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data.betaworks.com

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A Data Analysis of iTunes’ Top Charts Algorithm | dataworks

http://data.betaworks.com/data-analysis-itunes-top-charts-algorithm

A Data Analysis of iTunes’ Top Charts Algorithm. Jan 20, 2015 0 comments. A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com. Here’s the overview:. Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose. If these volatile days are deliberate, shouldn’t we be informed? These are people who pour coun...

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dataworks | data musings at betaworks

http://data.betaworks.com/page/2

The Definitive Difference between ‘Funny’ and ‘LOL. Sep 17, 2013 0 comments. I made a tappable version of my DataGotham talk. From Sept 9th, 2013. It goes through a number of ways in which we use graph analysis to find insight across different datasets. Digg Reader Visualized: what millions of RSS feeds look like. Jul 1, 2013 0 comments. In the following post we visualize two datasets representing RSS feeds. The first is a co-subscription network graph, including the top most subscribed feeds. Th...2) To...

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Israel, Gaza, War & Data | dataworks

http://data.betaworks.com/israel-gaza-war-data

Israel, Gaza, War & Data. By suman deb roy. Aug 26, 2014 0 comments. Chief scientist at betaworks wrote a recent post. That was featured by NPR, BBC and several other media. Gilad shows that Social Media is being actively used in the art of personalizing propaganda, and while war rages on the ground in Gaza and across Israeli skies, there’s an all-out information war unraveling in social networked spaces. Here are some highlights:. 8230; on social networks:. 8230; on algorithmic filtering:. 8230;and a be...

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No #MarchMadness Hate on Twitter? | dataworks

http://data.betaworks.com/no-marchmadness-hate-on-twitter

No #MarchMadness Hate on Twitter? Apr 4, 2014 0 comments. Last week the Digg editors came to us with an idea. Wouldn’t it be great if we could do a joint data post on March Madness, but instead of the usual – looking at the account with the most likes, or retweets – we would take a very different approach. Their idea was to find the most disliked team on social media, and map that out. March madness is a love / hate relationship. I hate it right now. Mdash; Dylan Lamb (@dylanlamb ) March 30, 2014. 8220;F...

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The Digital Flames of Ferguson | dataworks

http://data.betaworks.com/the-digital-flames-of-ferguson

The Digital Flames of Ferguson. By suman deb roy. Aug 26, 2014 0 comments. I wrote a recent post. Articulating the fragmentation around media coverage in Ferguson and the impact of social media in spreading news about events occurring in Ferguson, eventually gaining national attention. Using Twitter trending topics data, I show. How the country’s attention gradually turned to the events transpiring in Ferguson,. The driving factors and what it tells us about. Certain latent kinetics of the Social Web.

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dataworks | data musings at betaworks

A Data Analysis of iTunes’ Top Charts Algorithm. Jan 20, 2015 0 comments. A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com. Here’s the overview:. Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose. If these volatile days are deliberate, shouldn’t we be informed? These are people who pour coun...

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