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	<title>Pehr Hovey &#187; data visualization</title>
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	<link>http://pehrhovey.net/blog</link>
	<description>Interactive explorations</description>
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		<title>Aether: Exploring people who delete their tweets</title>
		<link>http://pehrhovey.net/blog/2010/07/aether-exploring-people-who-delete-their-tweets/</link>
		<comments>http://pehrhovey.net/blog/2010/07/aether-exploring-people-who-delete-their-tweets/#comments</comments>
		<pubDate>Sat, 31 Jul 2010 21:09:31 +0000</pubDate>
		<dc:creator>Pehr</dc:creator>
				<category><![CDATA[MAT Projects]]></category>
		<category><![CDATA[data visualization]]></category>
		<category><![CDATA[processing]]></category>
		<category><![CDATA[twitter]]></category>

		<guid isPermaLink="false">http://pehrhovey.net/blog/?p=696</guid>
		<description><![CDATA[I presented my masters project on June 9th, 2010 to complete my degree of M.S. Multimedia Engineering in the Media Arts &#38; Technology department at UCSB. I wanted to explore real-time data gathering and visualization and decided to use the Twitter API as the data source to see what I could do. My system consumes [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<title>Concepts for visualizing deleted tweets</title>
		<link>http://pehrhovey.net/blog/2010/05/concepts-for-visualizing-deleted-tweets/</link>
		<comments>http://pehrhovey.net/blog/2010/05/concepts-for-visualizing-deleted-tweets/#comments</comments>
		<pubDate>Wed, 26 May 2010 10:32:47 +0000</pubDate>
		<dc:creator>Pehr</dc:creator>
				<category><![CDATA[MAT Projects]]></category>
		<category><![CDATA[data visualization]]></category>
		<category><![CDATA[masters]]></category>
		<category><![CDATA[twitter]]></category>

		<guid isPermaLink="false">http://pehrhovey.net/blog/?p=687</guid>
		<description><![CDATA[My deleted tweet visualizations have been through several concepts that were practice for the real thing. I experimented with Parts-of-speech tagging, Automatic text classification and other tools in an effort to dig deeper into the tweets that people take back. Below are some prototypes that inspired the final product. Text categorization and tweet lifetime (how [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>Deleted Tweets: taking back what was said</title>
		<link>http://pehrhovey.net/blog/2010/04/deleted-tweets-taking-back-what-was-said/</link>
		<comments>http://pehrhovey.net/blog/2010/04/deleted-tweets-taking-back-what-was-said/#comments</comments>
		<pubDate>Thu, 22 Apr 2010 21:14:07 +0000</pubDate>
		<dc:creator>Pehr</dc:creator>
				<category><![CDATA[MAT Projects]]></category>
		<category><![CDATA[data visualization]]></category>
		<category><![CDATA[masters]]></category>
		<category><![CDATA[twitter]]></category>

		<guid isPermaLink="false">http://pehrhovey.net/blog/?p=681</guid>
		<description><![CDATA[For my master&#8217;s project I am looking at deleted Tweets. More specifically, I am catching tweets that have been marked deleted by their sender and visualizing how they connect to the user themselves. To make this all possible I had to make some software that gathers and stores a high volume of tweet data for [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>3D Data Visualization: Dewey Calendar</title>
		<link>http://pehrhovey.net/blog/2009/03/3d-data-visualization-dewey-calendar/</link>
		<comments>http://pehrhovey.net/blog/2009/03/3d-data-visualization-dewey-calendar/#comments</comments>
		<pubDate>Fri, 20 Mar 2009 08:19:45 +0000</pubDate>
		<dc:creator>Pehr</dc:creator>
				<category><![CDATA[MAT Projects]]></category>
		<category><![CDATA[data visualization]]></category>

		<guid isPermaLink="false">http://pehrhovey.net/blog/?p=234</guid>
		<description><![CDATA[The final project for MAT259: Algorithmic Data Visualization involved visualizing data in 3D. Since we are using Library data I chose to investigate the Dewey Decimal category information. The Dewey Decimal system places every item in one of 10 broad categories that each have many subcategories. I wanted to investigate how the distribution of Dewey [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<title>Visualizing Library Checkout Data in 2D Space</title>
		<link>http://pehrhovey.net/blog/2009/02/visualizing-library-checkout-data-ii-checkins-vs-checkouts/</link>
		<comments>http://pehrhovey.net/blog/2009/02/visualizing-library-checkout-data-ii-checkins-vs-checkouts/#comments</comments>
		<pubDate>Mon, 16 Feb 2009 10:19:22 +0000</pubDate>
		<dc:creator>Pehr</dc:creator>
				<category><![CDATA[MAT Projects]]></category>
		<category><![CDATA[data visualization]]></category>

		<guid isPermaLink="false">http://pehrhovey.net/blog/?p=219</guid>
		<description><![CDATA[The second project for MAT259: Data Visualization involved exploring two dimensional space for visualizing data from the Seattle Public Library. I was interested in getting away from the traditional chart mentality and displaying data in a more unique way. I settled on comparing two numerical quantities using a seesaw or balance/scale metaphor. I chose to [...]]]></description>
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		</item>
		<item>
		<title>Visualizing Library Checkout Data</title>
		<link>http://pehrhovey.net/blog/2009/01/visualizing-library-checkout-data/</link>
		<comments>http://pehrhovey.net/blog/2009/01/visualizing-library-checkout-data/#comments</comments>
		<pubDate>Sat, 24 Jan 2009 23:51:09 +0000</pubDate>
		<dc:creator>Pehr</dc:creator>
				<category><![CDATA[MAT Projects]]></category>
		<category><![CDATA[data visualization]]></category>

		<guid isPermaLink="false">http://pehrhovey.net/blog/?p=159</guid>
		<description><![CDATA[The first project for MAT259: Data Visualization involved exploring ways to display library checkout data in a 2D space. I chose to investigate how long each item was checked out and how it relates to item type, category or shelving section.  My goal was to be able to make qualitative judgements on how checkout duration [...]]]></description>
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