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	<title>Comments on: Quick Update from San Francisco</title>
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	<description>A community for the champions of Social Media and those seeking to learn</description>
	<pubDate>Thu, 20 Nov 2008 12:56:11 +0000</pubDate>
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		<title>By: Steveb</title>
		<link>http://www.socialmediaclub.org/2007/04/26/quick-update-from-san-francisco/#comment-15697</link>
		<dc:creator>Steveb</dc:creator>
		<pubDate>Fri, 27 Apr 2007 20:01:41 +0000</pubDate>
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		<description>I had an after thought from yesterdays meeting, and figured out what I value I extracted from the discussion.  A topic that was kind of alluded to is the network effect.  The value of a network depends on the number of people in the network - but a large network doesn't necessarily correspond to great value.  The extracted value really depends on common intent.  If you have people in the network who are "link whoring" then obviously they can dilute the value of your network.  On the other hand, those who are highly selective may prevent people from finding "un-thought of" value - don't we often find value in things we weren't seeking.  
It will be interesting when people do more in depth analysis of social networks and do what Google does with the world wide web.  The value of google is the algorithm by which it traverses the network of web pages and determines relevancy of search queries.  It extracts this value by weighting different properties of its nodes - content, outbound links, inbound links, etc.  If social networks are seen as platforms - and developers of individual networks provide APIs to expose metadata - then we would be able to programmatically traverse them and extract more value.  The corrollary thought is the issue of trust and privacy.  This would work just fine with public data - and dilution may not be an issue if we could filter our networks based on explicit criteria.  But still a lot depends on the willingness of participants to participate - as someone termed it, info karma.  But I like the idea of a common social network platform with open API's that will allow us to analyze and extract more value from them.  And maybe with that we could determine commonality from this social web to enhance the general search experience - example: selectively filter search result relevance based on  information extracted from the social network.</description>
		<content:encoded><![CDATA[<p>I had an after thought from yesterdays meeting, and figured out what I value I extracted from the discussion.  A topic that was kind of alluded to is the network effect.  The value of a network depends on the number of people in the network - but a large network doesn&#8217;t necessarily correspond to great value.  The extracted value really depends on common intent.  If you have people in the network who are &#8220;link whoring&#8221; then obviously they can dilute the value of your network.  On the other hand, those who are highly selective may prevent people from finding &#8220;un-thought of&#8221; value - don&#8217;t we often find value in things we weren&#8217;t seeking.<br />
It will be interesting when people do more in depth analysis of social networks and do what Google does with the world wide web.  The value of google is the algorithm by which it traverses the network of web pages and determines relevancy of search queries.  It extracts this value by weighting different properties of its nodes - content, outbound links, inbound links, etc.  If social networks are seen as platforms - and developers of individual networks provide APIs to expose metadata - then we would be able to programmatically traverse them and extract more value.  The corrollary thought is the issue of trust and privacy.  This would work just fine with public data - and dilution may not be an issue if we could filter our networks based on explicit criteria.  But still a lot depends on the willingness of participants to participate - as someone termed it, info karma.  But I like the idea of a common social network platform with open API&#8217;s that will allow us to analyze and extract more value from them.  And maybe with that we could determine commonality from this social web to enhance the general search experience - example: selectively filter search result relevance based on  information extracted from the social network.</p>
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