Geospatial Tweet Mapping

I have this love-hate relationship going on with Twitter. For starters, I hate the disproportionate amount of time it takes to manage the site for the value it creates. Marketers struggle with how much more time it takes to analyze campaign data (leads generated, mentions, retweets, followers gained, referrals, etc.) that uses Twitter as a communication channel to decide whether or not to employ the same techniques again for future campaigns. I love how the concept spurred lots of 3rd party app creators to make life easier using Twitter.

The idea that 140-character feeds could be so time consuming to manage and aggregate into meaningful data points is a challenge for most online marketers. The more apps that are created, the lazier marketers get in dealing with data. Like a multiverse gaming console, I just want a one-stop-aggregator for multiple platforms.. which means the ultimate, master API that thinks for itself, automatically adjusts to accept new connections and ports many data formats into one cloud repository. The latter incarnations actually exist. For now, we have to rely on and contend with the more sluggish, manual human interface.

Because the public sector is always shorthanded, much of the data aggregation comes from outside sources using non-standard perimeters. Even how coordinates are stored have three or four different formats. Ever look at a physical topo map for hiking? The degree and UTM systems are both listed. Google Maps uses the decimal system. Anyhow. Geospatial analysis (GIS) typically refers to sets of longitude/latitude location markers designated to individual data points and was originally developed to help solve problems in environmental and life sciences, ecology, geology, and epidemiology. It has expanded to include a lot more industries like defense, intelligence, utilities, natural resources, social sciences, public safety, etc. Marketers use geospatial data to target customer segments that are based in certain zip codes, cities, or metropolitan areas, though largely for direct marketing efforts.

Here are a few geospatial web tools for Twitter trend watching:
Here are a few examples of geospatial mapping using Twitter data:
Here's a BHAG (big hairy audacious goal) to ponder about. Hardly anyone is going to contribute public data without a benefit in return. Let's say that you own a parking structure that is adjacent to a hotel or a shopping district. Wouldn't it be in your interest to log the check-ins at the structure and make that data available to nearby establishments via RSS or Twitter feed? It would deduct from a fixed number of spaces how many vehicles are parked there, updating every five to ten minutes. It might be a spammy channel but end-users would just have to visit, not subscribe to, a parking structure's online site feed to see if there was parking available. A tool like this would have been tremendously helpful on the weekend of the Northwest Food Service Tradeshow since there were multiple large events and a marathon being held near the Oregon Convention Center and it took more than a half hour to find adjacent parking. It's a winning outcome for everyone. The parking structure would get to maximize occupancy, the convention center/nearby shops/hotels would have more bodies inside for point-of-sale transactions, and the visiting end-users would be able to get on their day instead of driving around in circles in downtown Portland.
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