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	<title>The Bolin Marketing Blog &#187; emotion</title>
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	<description>Ideas, viewpoints and insights from the Bolin Marketing Team</description>
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		<title>Time. Location. Emotion.</title>
		<link>http://bolindigital.com/time-location-emotion</link>
		<comments>http://bolindigital.com/time-location-emotion#comments</comments>
		<pubDate>Mon, 09 Mar 2009 17:22:52 +0000</pubDate>
		<dc:creator>Paul Saarinen</dc:creator>
				<category><![CDATA[Social Media]]></category>
		<category><![CDATA[collectiveness]]></category>
		<category><![CDATA[conscious]]></category>
		<category><![CDATA[emotion]]></category>
		<category><![CDATA[location]]></category>
		<category><![CDATA[subconscious]]></category>
		<category><![CDATA[time]]></category>
		<category><![CDATA[twitter]]></category>

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		<description><![CDATA[It&#8217;s about 4 or 5 PM last Thursday, and I&#8217;m sitting on my couch at home suffering from a low grade fever of 101 degrees, and a thought occurs to me. Well, it&#8217;s the thought illustrated in my little diagram above. I always tend to think of data, and how it can be used through [...]
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			<content:encoded><![CDATA[<p></p><p>It&#8217;s about 4 or 5 PM last Thursday, and I&#8217;m sitting on my couch at home suffering from a low grade fever of 101 degrees, and a thought occurs to me.   Well, it&#8217;s the thought illustrated in my little diagram above.  I always tend to think of data, and how it can be used through a marketing filter.  This is my first of many problems.  In order to try and understand the diagram above, I had to forget those thoughts&#8230;at least for a few hours.</p>
<p>We now can bring three seemingly unconnected, but readily available data points together, and look for connections in a whole new layer.  Are there implications, or will anything be on the other side?  I&#8217;m trying to get my small brain to wrap around something much larger than I can swallow.  I guess what I&#8217;m trying to peer into, is a collective consciousness, and how it relates to real world events.</p>
<p>Step 1. Gather Twitter api search feed.<br />
Step 2. Utilize GPS coordinates for tweets that have them, or sub in location profile data for those that don&#8217;t have GPS data.<br />
Step 3. Parse each 140 character tweet for emotional trigger word and give a value (this will be tricky, and pretty loose)<br />
Step 4. Use open source heat map API synced with Google Maps API to visualize impact<br />
Step 5. Start looking for patterns with real world events (I have a few ideas on this)<br />
Step 6. Determine if the patterns prove out over multiple occurences</p>
<p>Well, that&#8217;s as far as I have gone.  What are your thoughts?</p>

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