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	<title>Comments on: Bay Area R User Group 2009 Kickoff Video</title>
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	<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/</link>
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		<title>By: &#124; LectureMaker, LLC</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-584</link>
		<dc:creator>&#124; LectureMaker, LLC</dc:creator>
		<pubDate>Mon, 14 Sep 2009 07:00:14 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-584</guid>
		<description>[...] The Science of Predictive Analytics [...]</description>
		<content:encoded><![CDATA[<p>[...] The Science of Predictive Analytics [...]</p>
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		<title>By: How Google and Facebook are using R :Health Fitness Wealth</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-189</link>
		<dc:creator>How Google and Facebook are using R :Health Fitness Wealth</dc:creator>
		<pubDate>Sat, 18 Jul 2009 22:31:24 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-189</guid>
		<description>[...] (March 26th Update: Video now available)  Last night, I moderated our Bay Area R Users Group kick-off event with a panel discussion entitled &#8220;The R and Science of Predictive Analytics&#8221;, co-located with the  Predictive Analytics World  conference here in SF. [...]</description>
		<content:encoded><![CDATA[<p>[...] (March 26th Update: Video now available)  Last night, I moderated our Bay Area R Users Group kick-off event with a panel discussion entitled &#8220;The R and Science of Predictive Analytics&#8221;, co-located with the  Predictive Analytics World  conference here in SF. [...]</p>
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		<title>By: Crossing Arbogast</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-186</link>
		<dc:creator>Crossing Arbogast</dc:creator>
		<pubDate>Thu, 09 Jul 2009 06:30:22 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-186</guid>
		<description>Thanks for this Nice post, Really usefull all of us. just bookmarked this post in my digg profile, hope you will update more post soon.
I really liked your blog!

Regards,
Shaza</description>
		<content:encoded><![CDATA[<p>Thanks for this Nice post, Really usefull all of us. just bookmarked this post in my digg profile, hope you will update more post soon.<br />
I really liked your blog!</p>
<p>Regards,<br />
Shaza</p>
]]></content:encoded>
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		<title>By: Video Rig &#171; LectureMaker</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-120</link>
		<dc:creator>Video Rig &#171; LectureMaker</dc:creator>
		<pubDate>Tue, 19 May 2009 09:33:40 +0000</pubDate>
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		<description>[...] Link  to this video [...]</description>
		<content:encoded><![CDATA[<p>[...] Link  to this video [...]</p>
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		<title>By: Embedded Components and Tools Blog Center &#187; Blog Archive &#187; Bay Area R User Group 2009 Kickoff Video</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-66</link>
		<dc:creator>Embedded Components and Tools Blog Center &#187; Blog Archive &#187; Bay Area R User Group 2009 Kickoff Video</dc:creator>
		<pubDate>Thu, 02 Apr 2009 18:41:08 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-66</guid>
		<description>[...] Learn more and watch lecture [...]</description>
		<content:encoded><![CDATA[<p>[...] Learn more and watch lecture [...]</p>
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		<title>By: Michael Batty</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-60</link>
		<dc:creator>Michael Batty</dc:creator>
		<pubDate>Sun, 29 Mar 2009 22:01:25 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-60</guid>
		<description>very interesting

here is some other stuff we have done

Mike

&lt;a href=&quot;http://www.nature.com/nature/journal/v444/n7119/abs/nature05302.html&quot; rel=&quot;nofollow&quot;&gt;Rank clocks&lt;/a&gt;


&lt;a href=&quot;http://www.springerlink.com/content/t42871v22396j04q/&quot; rel=&quot;nofollow&quot;&gt;Hierarchy in Cities and City Systems&lt;/a&gt;</description>
		<content:encoded><![CDATA[<p>very interesting</p>
<p>here is some other stuff we have done</p>
<p>Mike</p>
<p><a href="http://www.nature.com/nature/journal/v444/n7119/abs/nature05302.html" rel="nofollow">Rank clocks</a></p>
<p><a href="http://www.springerlink.com/content/t42871v22396j04q/" rel="nofollow">Hierarchy in Cities and City Systems</a></p>
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		<title>By: admin</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-58</link>
		<dc:creator>admin</dc:creator>
		<pubDate>Sat, 28 Mar 2009 19:45:05 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-58</guid>
		<description>I was particularly impressed with how common the &lt;em&gt;power law distribution&lt;/em&gt; is used to characterize and predict online user behavior within a well defined ecosystem such as facebook.

&lt;strong&gt;power law distribution&lt;/strong&gt;

[pmath]P(x)=Kx^alpha[/pmath],

Where:

[pmath]P(x) right [/pmath] size of an event, such as users who stay on facebook more than three weeks
[pmath]x right [/pmath] property of an event, such as number of users who join facebook per day
[pmath]alpha right [/pmath] some parameter of the distribution, such as the percent of users who enter their gender during new user registration
[pmath]K right [/pmath] a scaling constant

So the size of a community event, [pmath]P(x)[/pmath], can be predicted with the power law distribution. The problem might reduce down to the selection of the right parameter [pmath]alpha[/pmath] and scaling constant [pmath]K[/pmath] to apply to the properties characterized by [pmath]x[/pmath]. The correlation measured from historical data can then be used to determine if further on-site changes could be made to improve performance from an online community.  

R then becomes the statistics tool to crunch data, calculate, and plot distributions.  Then the results from R can be used to predict and improve future online behavior with new community policies or a change in applications.  Neat.

Management of large amounts of data was discussed throughout the lecture. One solution is in the open-source cloud initiative called Hadoop. 

Notes: &lt;ol&gt;

	&lt;li&gt;LectureMaker supports math publishing, both in its blog posts and in its comments. See my wordpress plugin to learn more, called &lt;a href=&quot;http://wordpress.org/extend/plugins/wpmathpub/&quot; rel=&quot;nofollow&quot;&gt;wpmathpub&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;Itamar made reference to &lt;a href=&quot;http://hadoop.apache.org/core/&quot; rel=&quot;nofollow&quot;&gt;Hadoop&lt;/a&gt; as one way the facebook data team manages large amounts of data for R projects

	&lt;/li&gt;&lt;li&gt;I had to look up &quot;what is a power law distribution&quot; as it applies to social networks. Here is the reference I choose to rely upon &lt;a href=&quot;http://www.isoc.org/inet2000/cdproceedings/2a/2a_2.htm#s7&quot; rel=&quot;nofollow&quot;&gt;Power Law Distributions in Real and Virtual Worlds&lt;/a&gt; by Narushige SHIODE and Michael BATTY, University College London
&lt;/li&gt;
&lt;/ol&gt;</description>
		<content:encoded><![CDATA[<p>I was particularly impressed with how common the <em>power law distribution</em> is used to characterize and predict online user behavior within a well defined ecosystem such as facebook.</p>
<p><strong>power law distribution</strong></p>
<p><img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_986.5_5fd9849a10e14f4b0ae6cb8fb28cd243.png" style="vertical-align:-13.5px; display: inline-block ;" alt="P(x)=Kx^alpha" title="P(x)=Kx^alpha"/>,</p>
<p>Where:</p>
<p><img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_986.5_c9cfffd189fc4b8631357079c3dbebda.png" style="vertical-align:-13.5px; display: inline-block ;" alt="P(x) right" title="P(x) right"/> size of an event, such as users who stay on facebook more than three weeks<br />
<img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_994.5_d339f3a6f3c23ed45537703fc47d03e0.png" style="vertical-align:-5.5px; display: inline-block ;" alt="x right" title="x right"/> property of an event, such as number of users who join facebook per day<br />
<img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_994.5_0523f92edd7aa3da94ce03c096d0b1af.png" style="vertical-align:-5.5px; display: inline-block ;" alt="alpha right" title="alpha right"/> some parameter of the distribution, such as the percent of users who enter their gender during new user registration<br />
<img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_994.5_1f77d8062246cd0275070becb35df9e9.png" style="vertical-align:-5.5px; display: inline-block ;" alt="K right" title="K right"/> a scaling constant</p>
<p>So the size of a community event, <img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_986.5_d1999f23a87281d3077516f93d7abf77.png" style="vertical-align:-13.5px; display: inline-block ;" alt="P(x)" title="P(x)"/>, can be predicted with the power law distribution. The problem might reduce down to the selection of the right parameter <img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_994.5_d50f9308cbed63f78681eb5d428d5a8d.png" style="vertical-align:-5.5px; display: inline-block ;" alt="alpha" title="alpha"/> and scaling constant <img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_994.5_4d6da139270047fbdbdf5351a0bc1ccb.png" style="vertical-align:-5.5px; display: inline-block ;" alt="K" title="K"/> to apply to the properties characterized by <img src="http://www.lecturemaker.com/wp-content/plugins/wpmathpub/phpmathpublisher/img/math_994.5_137b8dad9acade63b507e67878d3b94b.png" style="vertical-align:-5.5px; display: inline-block ;" alt="x" title="x"/>. The correlation measured from historical data can then be used to determine if further on-site changes could be made to improve performance from an online community.  </p>
<p>R then becomes the statistics tool to crunch data, calculate, and plot distributions.  Then the results from R can be used to predict and improve future online behavior with new community policies or a change in applications.  Neat.</p>
<p>Management of large amounts of data was discussed throughout the lecture. One solution is in the open-source cloud initiative called Hadoop. </p>
<p>Notes:
<ol>
<li>LectureMaker supports math publishing, both in its blog posts and in its comments. See my wordpress plugin to learn more, called <a href="http://wordpress.org/extend/plugins/wpmathpub/" rel="nofollow">wpmathpub</a></li>
<li>Itamar made reference to <a href="http://hadoop.apache.org/core/" rel="nofollow">Hadoop</a> as one way the facebook data team manages large amounts of data for R projects
</li>
<li>I had to look up &#8220;what is a power law distribution&#8221; as it applies to social networks. Here is the reference I choose to rely upon <a href="http://www.isoc.org/inet2000/cdproceedings/2a/2a_2.htm#s7" rel="nofollow">Power Law Distributions in Real and Virtual Worlds</a> by Narushige SHIODE and Michael BATTY, University College London
</li>
</ol>
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		<title>By: How Google and Facebook are using R : Data Evolution</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-57</link>
		<dc:creator>How Google and Facebook are using R : Data Evolution</dc:creator>
		<pubDate>Thu, 26 Mar 2009 10:17:00 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-57</guid>
		<description>[...] Update: Video now available! Last night, I moderated our Bay Area R Users Group kick-off event with a panel discussion entitled &#8220;The R and Science of Predictive Analytics&#8221;, co-located with the  Predictive Analytics World  conference here in SF. [...]</description>
		<content:encoded><![CDATA[<p>[...] Update: Video now available! Last night, I moderated our Bay Area R Users Group kick-off event with a panel discussion entitled &#8220;The R and Science of Predictive Analytics&#8221;, co-located with the  Predictive Analytics World  conference here in SF. [...]</p>
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		<title>By: Michael E. Driscoll</title>
		<link>http://www.lecturemaker.com/2009/02/r-kickoff-video/comment-page-1/#comment-56</link>
		<dc:creator>Michael E. Driscoll</dc:creator>
		<pubDate>Thu, 26 Mar 2009 10:12:20 +0000</pubDate>
		<guid isPermaLink="false">http://www.lecturemaker.com/2009/02/r-and-science-of-predictive-analytics-lecture-production/#comment-56</guid>
		<description>Hi Ron - Many thanks for putting this together - the video looks great!  I particularly like the way you&#039;ve allowed browsing of the content with the red status bars below.  Look forward to more great stuff in the future.

Mike</description>
		<content:encoded><![CDATA[<p>Hi Ron &#8211; Many thanks for putting this together &#8211; the video looks great!  I particularly like the way you&#8217;ve allowed browsing of the content with the red status bars below.  Look forward to more great stuff in the future.</p>
<p>Mike</p>
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