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Twitter Vote Report monitors the US election via micro-blogging

Description: Discriminating officials, fraudulent voting machines or simply long wait times are some of the problems voters may be facing on November 4th. Twitter Vote Report gives American voters an opportunity to report incidents on Election Day using their mobile phones and share them with others.

Digital Tools Being Used: Mobile phones, Twitter, Google Maps mashup, Plodt, iPhone app.

What Are They Doing: Twitter Vote Report aggregates short messages from people all over the US during the election.

Twitterers can use the hash tag “votereport” to let Twitter Vote Report know about an incident. But reports can also be submitted by sending a SMS to the organizers, using an iPhone / Android app or simply calling them.

Twitter Vote Report will aggregate all messages sent to them and display them on their front page. They also offer a RSS feed for those who want to receive all the messages. But to make more use of the information sent in, Twitter Vote Report offers some additional tags that can be added to a tweet to indicate a specific problem:

• #[zip code] to indicate the zip code where you’re voting; ex., “#12345″

• L:[address or city] to drill down to your exact location; ex. “L:1600 Pennsylvania Avenue DC”

• #machine for machine problems; ex., “#machine broken, using prov. ballot”

• #reg for registration troubles; ex., “#reg I wasn’t on the rolls”

• #wait:[minutes] for long lines; ex., “#wait:120 and I’m coming back later”

• #early if you’re voting before November 4th

• #good or #bad to give a quick sense of your overall experience

• #EP[your state] if you have a serious problem and need help from the Election Protection coalition; ex., #EPOH

They use the information submitted this way to provide some more interesting services. The geo tags are used to visualize the position of the submitters on a Google Maps mashup. According to the Twitter Vote report some features are still in development, including one to visualize where wait times are the longest.
The latter information is one which can already be derived from a Plodt chart which uses the “#wait” tagged messages as a source.