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	<title>Comments on: The Confounding Variable Of The Retweet</title>
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	<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/</link>
	<description>Gaining Insight From Social Media Data</description>
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		<title>By: You Got It All Wrong: The Limits of Social Media Monitoring &#124; BrandSavant</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-1416</link>
		<dc:creator>You Got It All Wrong: The Limits of Social Media Monitoring &#124; BrandSavant</dc:creator>
		<pubDate>Mon, 14 Feb 2011 12:41:59 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-1416</guid>
		<description>[...] Well, it isn&#8217;t really your fault. I&#8217;m also not going to beat up on the tool &#8211; it was built to track mentions, and I have no reason to believe that it didn&#8217;t do an admirable job (so, Meltwater folks, stand down &#8211; this isn&#8217;t about you.) The issue here is that you were asked the wrong question. Tracking mentions for predictive purposes is of dubious value &#8211; in the short term, the volume of mentions is a random walk. [...]</description>
		<content:encoded><![CDATA[<p>[...] Well, it isn&#8217;t really your fault. I&#8217;m also not going to beat up on the tool &#8211; it was built to track mentions, and I have no reason to believe that it didn&#8217;t do an admirable job (so, Meltwater folks, stand down &#8211; this isn&#8217;t about you.) The issue here is that you were asked the wrong question. Tracking mentions for predictive purposes is of dubious value &#8211; in the short term, the volume of mentions is a random walk. [...]</p>
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		<title>By: Understanding Klout &#124; BrandSavant</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-1142</link>
		<dc:creator>Understanding Klout &#124; BrandSavant</dc:creator>
		<pubDate>Tue, 19 Oct 2010 14:53:40 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-1142</guid>
		<description>[...] If we are interested in the realm of influence beyond the easy, immediate measures (like the confounding variable of the retweet) then the amount of data mining required presents what may currently be an intractable [...]</description>
		<content:encoded><![CDATA[<p>[...] If we are interested in the realm of influence beyond the easy, immediate measures (like the confounding variable of the retweet) then the amount of data mining required presents what may currently be an intractable [...]</p>
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		<title>By: Twitter&#8217;s Most Elusive Statistic &#124; BrandSavant</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-965</link>
		<dc:creator>Twitter&#8217;s Most Elusive Statistic &#124; BrandSavant</dc:creator>
		<pubDate>Mon, 13 Sep 2010 14:23:17 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-965</guid>
		<description>[...] the vast majority of those followers realize the question is rhetorical. (I admit there is also the confounding variable of the retweet to deal with here, but engagement also comes into play in retweet [...]</description>
		<content:encoded><![CDATA[<p>[...] the vast majority of those followers realize the question is rhetorical. (I admit there is also the confounding variable of the retweet to deal with here, but engagement also comes into play in retweet [...]</p>
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		<title>By: &#8220;Unaided Recall&#8221; in Social Media Research &#124; BrandSavant</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-892</link>
		<dc:creator>&#8220;Unaided Recall&#8221; in Social Media Research &#124; BrandSavant</dc:creator>
		<pubDate>Mon, 30 Aug 2010 15:24:50 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-892</guid>
		<description>[...] the folks monitoring for those keywords will dutifully tally this up as a &#8220;mention&#8221; (which is, as I&#8217;ve noted previously, a dubious metric anyway.) However, it&#8217;s actually a little bit more than that &#8211; it&#8217;s an unaided mention. [...]</description>
		<content:encoded><![CDATA[<p>[...] the folks monitoring for those keywords will dutifully tally this up as a &#8220;mention&#8221; (which is, as I&#8217;ve noted previously, a dubious metric anyway.) However, it&#8217;s actually a little bit more than that &#8211; it&#8217;s an unaided mention. [...]</p>
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		<title>By: Tom Messett</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-418</link>
		<dc:creator>Tom Messett</dc:creator>
		<pubDate>Sat, 08 May 2010 13:21:18 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-418</guid>
		<description>Hi Tom, nice post, I used to work for a monitoring service so I know exactly what you mean about the RT issue and couldn&#039;t agree more! Anyway, I am really interested to learn more about your thoughts on the &quot;Eavesdrop Pitch&quot;?</description>
		<content:encoded><![CDATA[<p>Hi Tom, nice post, I used to work for a monitoring service so I know exactly what you mean about the RT issue and couldn&#8217;t agree more! Anyway, I am really interested to learn more about your thoughts on the &#8220;Eavesdrop Pitch&#8221;?</p>
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		<title>By: Dennis McDonald</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-416</link>
		<dc:creator>Dennis McDonald</dc:creator>
		<pubDate>Wed, 05 May 2010 16:17:25 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-416</guid>
		<description>Here are some additional concern about social media metrics, or rather, not with the metrics themselves but how they might be used in some cases: &quot;OMB&#039;s New Guidance on Social Media is an Improvement - But There&#039;s a Catch&quot; http://www.ddmcd.com/guidance.html</description>
		<content:encoded><![CDATA[<p>Here are some additional concern about social media metrics, or rather, not with the metrics themselves but how they might be used in some cases: &#8220;OMB&#8217;s New Guidance on Social Media is an Improvement &#8211; But There&#8217;s a Catch&#8221; <a href="http://www.ddmcd.com/guidance.html" rel="nofollow">http://www.ddmcd.com/guidance.html</a></p>
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		<title>By: Dennis McDonald</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-415</link>
		<dc:creator>Dennis McDonald</dc:creator>
		<pubDate>Wed, 05 May 2010 16:06:11 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-415</guid>
		<description>I&#039;m not dismissing social media monitoring statistics; they can be of great use. My concern has to do with how easy or hard it is to relate the different categories they use to other (e.g., known or documented) population statistics. Having recently evaluated several different monitoring tools I thought they could be doing a better job on things like making their population categorization rules and processes more transparent.</description>
		<content:encoded><![CDATA[<p>I&#8217;m not dismissing social media monitoring statistics; they can be of great use. My concern has to do with how easy or hard it is to relate the different categories they use to other (e.g., known or documented) population statistics. Having recently evaluated several different monitoring tools I thought they could be doing a better job on things like making their population categorization rules and processes more transparent.</p>
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		<title>By: Tom Webster</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-414</link>
		<dc:creator>Tom Webster</dc:creator>
		<pubDate>Wed, 05 May 2010 14:48:21 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-414</guid>
		<description>Dennis - I&#039;m with you, especially because I am currently a sample-survey-and-statistics guy myself. Yet I am reluctant to dismiss social media monitoring metrics, especially when half the US population is using social networks. Yes, the non-response bias is troubling, but I think the answer is the continued application of sound sampling techniques (properly weighting sources and samples, for instance) within the framework of a structured monitoring program. There&#039;s a there there, though yes, it needs some work :)</description>
		<content:encoded><![CDATA[<p>Dennis &#8211; I&#8217;m with you, especially because I am currently a sample-survey-and-statistics guy myself. Yet I am reluctant to dismiss social media monitoring metrics, especially when half the US population is using social networks. Yes, the non-response bias is troubling, but I think the answer is the continued application of sound sampling techniques (properly weighting sources and samples, for instance) within the framework of a structured monitoring program. There&#8217;s a there there, though yes, it needs some work <img src='http://brandsavant.com/wp-includes/images/smilies/icon_smile.gif' alt=':)' class='wp-smiley' /> </p>
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	<item>
		<title>By: Dennis McDonald</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-413</link>
		<dc:creator>Dennis McDonald</dc:creator>
		<pubDate>Wed, 05 May 2010 14:42:28 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-413</guid>
		<description>Excellent post.

I&#039;m less concerned about the inconsistency of &quot;sentiment analysis&quot; than I am about the underlying population numbers and what they represent. As a former sample-survey-and-statistics guy I&#039;m especially sensitive to what populations the measures of mentions and conversations are referring to and whether it&#039;s possible to relate the conversation metrics to known populations. 

Sometimes this is not a problem if you are primarily looking at an entry point into conversations. But if you&#039;re tracking, say, how well a government program or a new product introduction is performing with a particular population or market segment, the lack of a definable and measurable connection between conversation and population can be a big problem.</description>
		<content:encoded><![CDATA[<p>Excellent post.</p>
<p>I&#8217;m less concerned about the inconsistency of &#8220;sentiment analysis&#8221; than I am about the underlying population numbers and what they represent. As a former sample-survey-and-statistics guy I&#8217;m especially sensitive to what populations the measures of mentions and conversations are referring to and whether it&#8217;s possible to relate the conversation metrics to known populations. </p>
<p>Sometimes this is not a problem if you are primarily looking at an entry point into conversations. But if you&#8217;re tracking, say, how well a government program or a new product introduction is performing with a particular population or market segment, the lack of a definable and measurable connection between conversation and population can be a big problem.</p>
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		<title>By: Hugo from Zeta</title>
		<link>http://brandsavant.com/the-confounding-variable-of-the-retweet/comment-page-1/#comment-410</link>
		<dc:creator>Hugo from Zeta</dc:creator>
		<pubDate>Tue, 04 May 2010 13:46:53 +0000</pubDate>
		<guid isPermaLink="false">http://brandsavant.com/?p=525#comment-410</guid>
		<description>Great post! Modern monitoring tools are simply not sophisticated enough to deliver quality sentiment scoring. That&#039;s why it&#039;s crucial to use some good, old-fashioned elbow grease when analyzing social media data.</description>
		<content:encoded><![CDATA[<p>Great post! Modern monitoring tools are simply not sophisticated enough to deliver quality sentiment scoring. That&#8217;s why it&#8217;s crucial to use some good, old-fashioned elbow grease when analyzing social media data.</p>
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