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	<title>Comments on: What Is Automated Sentiment Analysis Good For?</title>
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	<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/</link>
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		<title>By: human mathematics</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-44</link>
		<dc:creator>human mathematics</dc:creator>
		<pubDate>Fri, 23 Sep 2011 02:19:18 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-44</guid>
		<description>Thank you for a dose of common sense here! Sentiment analysis is such a f***ing buzzword. You know, with only two polarities (+/−), 80% should not be compared to 0%, it should be compared to 50%.

Also ask yourself this: what&#039;s the likelihood that they get 5 out of 5 correct? That&#039;s

.8^5 = 0.32768

or compared to random guessing, 

.3^5 = 0.00243


Do people not know Bayesian statistics? Even 99% correct is not that good of a score in some situations.</description>
		<content:encoded><![CDATA[<p>Thank you for a dose of common sense here! Sentiment analysis is such a f***ing buzzword. You know, with only two polarities (+/−), 80% should not be compared to 0%, it should be compared to 50%.</p>
<p>Also ask yourself this: what&#8217;s the likelihood that they get 5 out of 5 correct? That&#8217;s</p>
<p>.8^5 = 0.32768</p>
<p>or compared to random guessing, </p>
<p>.3^5 = 0.00243</p>
<p>Do people not know Bayesian statistics? Even 99% correct is not that good of a score in some situations.</p>
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		<title>By: Bruce</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-33</link>
		<dc:creator>Bruce</dc:creator>
		<pubDate>Wed, 19 May 2010 14:21:00 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-33</guid>
		<description>[...] The original post that initiated the conversation  why sentiment analysis sucks for social media monitoring (attempt 1) [...]</description>
		<content:encoded><![CDATA[<p>[...] The original post that initiated the conversation  why sentiment analysis sucks for social media monitoring (attempt 1) [...]</p>
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		<title>By: Balamurali A R</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-19</link>
		<dc:creator>Balamurali A R</dc:creator>
		<pubDate>Fri, 09 Apr 2010 07:03:53 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-19</guid>
		<description>I did not read the first link but my analysis is from the above post only. 

I totally disagree to the fact that sentiment analysis is having an accuracy of only 80%. Its way more higher. The real problem is not the accuracy but the social indifference of the business to accept this technology. When an marketing agency(manual) gives analysis they (clients accept) but the same thing when a machine does they petrify it. Why? 

When OCR (optical character recognition) came in 60&#039;s, everybody said it wouldnt work. But right now entire US postal service works on it. And to add some more info - the system is only 97% accurate, meaning for every 100 mails, 3 mails do not reach their intended recipient. And still I see the people using it. SA is just novice compared to OCR, may be 7 yrs or so - give it some time, its surely going to be  buck maker.</description>
		<content:encoded><![CDATA[<p>I did not read the first link but my analysis is from the above post only. </p>
<p>I totally disagree to the fact that sentiment analysis is having an accuracy of only 80%. Its way more higher. The real problem is not the accuracy but the social indifference of the business to accept this technology. When an marketing agency(manual) gives analysis they (clients accept) but the same thing when a machine does they petrify it. Why? </p>
<p>When OCR (optical character recognition) came in 60&#8217;s, everybody said it wouldnt work. But right now entire US postal service works on it. And to add some more info &#8211; the system is only 97% accurate, meaning for every 100 mails, 3 mails do not reach their intended recipient. And still I see the people using it. SA is just novice compared to OCR, may be 7 yrs or so &#8211; give it some time, its surely going to be  buck maker.</p>
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		<title>By: Why Sentiment Analysis Sucks for Social Media Monitoring &#124; Seven Day Workweek</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-12</link>
		<dc:creator>Why Sentiment Analysis Sucks for Social Media Monitoring &#124; Seven Day Workweek</dc:creator>
		<pubDate>Wed, 31 Mar 2010 21:43:17 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-12</guid>
		<description>[...] The original post that initiated the conversation  why sentiment analysis sucks for social media monitoring (attempt 1) [...]</description>
		<content:encoded><![CDATA[<p>[...] The original post that initiated the conversation  why sentiment analysis sucks for social media monitoring (attempt 1) [...]</p>
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		<title>By: Maria Ogneva</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-10</link>
		<dc:creator>Maria Ogneva</dc:creator>
		<pubDate>Tue, 09 Mar 2010 04:21:44 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-10</guid>
		<description>Thanks for asking the tough questions. 

I agree with Amber on this one. First of all, sentiment should be used to take a pulse, and never as the sole indicator of brand health. Secondly, it will give you an fairly accurate net sentiment score, but if you want to know the sentiment of an article, you should just read it. No automated tool will ever be better than a human, because our speech is way too nuanced (two people agree about sentiment only 79% of the time, so no automated tool can be better than that). Putting a human brain behind it to interpret, and then engage appropriately, is the name of the game.

Maria Ogneva
Biz360
@themaria @biz360</description>
		<content:encoded><![CDATA[<p>Thanks for asking the tough questions. </p>
<p>I agree with Amber on this one. First of all, sentiment should be used to take a pulse, and never as the sole indicator of brand health. Secondly, it will give you an fairly accurate net sentiment score, but if you want to know the sentiment of an article, you should just read it. No automated tool will ever be better than a human, because our speech is way too nuanced (two people agree about sentiment only 79% of the time, so no automated tool can be better than that). Putting a human brain behind it to interpret, and then engage appropriately, is the name of the game.</p>
<p>Maria Ogneva<br />
Biz360<br />
@themaria @biz360</p>
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		<title>By: Amber Naslund</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-9</link>
		<dc:creator>Amber Naslund</dc:creator>
		<pubDate>Mon, 08 Mar 2010 15:51:33 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-9</guid>
		<description>Hi Mikko -

Some great thoughts in here. And it&#039;s part of the reason why we haven&#039;t hammered home sentiment as the end-all-be-all of social media analysis, because, well, it can&#039;t be.

Sentiment can have broad applications for things like trends, but if and ONLY if a business is committed to putting a human brain behind the first pass automated results. That means that only a person can understand and interpret things like sarcasm, slang, and other nuances of the human language. 

And no matter HOW good the technologies get, there&#039;s no one other than a human that can connect the sentiment trend data to the business goals they&#039;ve set. 75% positive reactions to our product means...what, exactly? What are we going to DO with that information? That&#039;s really the key for applying ANY piece of data, and sentiment indicators are no different in that regard.

Thanks for some thought provoking dialogue. Always happy to chat further.

Cheers,
Amber Naslund, Radian6
@ambercadabra</description>
		<content:encoded><![CDATA[<p>Hi Mikko -</p>
<p>Some great thoughts in here. And it&#8217;s part of the reason why we haven&#8217;t hammered home sentiment as the end-all-be-all of social media analysis, because, well, it can&#8217;t be.</p>
<p>Sentiment can have broad applications for things like trends, but if and ONLY if a business is committed to putting a human brain behind the first pass automated results. That means that only a person can understand and interpret things like sarcasm, slang, and other nuances of the human language. </p>
<p>And no matter HOW good the technologies get, there&#8217;s no one other than a human that can connect the sentiment trend data to the business goals they&#8217;ve set. 75% positive reactions to our product means&#8230;what, exactly? What are we going to DO with that information? That&#8217;s really the key for applying ANY piece of data, and sentiment indicators are no different in that regard.</p>
<p>Thanks for some thought provoking dialogue. Always happy to chat further.</p>
<p>Cheers,<br />
Amber Naslund, Radian6<br />
@ambercadabra</p>
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		<title>By: Mike Layton</title>
		<link>http://www.sevendayworkweek.com/web-analytics-tools/what-is-automated-sentiment-analysis-good-for/#comment-8</link>
		<dc:creator>Mike Layton</dc:creator>
		<pubDate>Mon, 08 Mar 2010 14:39:50 +0000</pubDate>
		<guid isPermaLink="false">http://www.sevendayworkweek.com/?p=168#comment-8</guid>
		<description>I think a huge problem with the acceptance of sentiment analysis is that many do not think about what a 20% error rate (at best) really means. Your example goes a long way in demonstrating the importance of accuracy. While we see value in sentiment if coded correctly (via real people), it is a surface metric. The real insight comes from understanding *why* sentiment is positive or negative, especially in relation to the competition. Excellent post.

Thanks for sharing, Mike.</description>
		<content:encoded><![CDATA[<p>I think a huge problem with the acceptance of sentiment analysis is that many do not think about what a 20% error rate (at best) really means. Your example goes a long way in demonstrating the importance of accuracy. While we see value in sentiment if coded correctly (via real people), it is a surface metric. The real insight comes from understanding *why* sentiment is positive or negative, especially in relation to the competition. Excellent post.</p>
<p>Thanks for sharing, Mike.</p>
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