Make money by embedding data in Twitter messages

When data can be formally embedded in Twitter messages, we see enormous new opportunities for data mining, social data distribution, and intelligent application behavior unlimited by lack of natural language processing technology. Best of all, the richness of this data is available to everyone, and can be sent and consumed by both humans and machines.

How it works

A user (or her agent, like his Twitter client) sends a Twitter message that includes semi-structured embedded data, like @romeo $loves @juliet
This message is distributed like any other Twitter message to the user's followers
The followers' Twitter clients listen for messages with embedded data and extract data they understand. This data is presented to users, recorded, or otherwise consumed in some useful way.
Data mining applications extract data from messages using the Twitter platform (for example, using search or the public timeline) and then process it, present it, or otherwise consume it in some way useful to humans or other applications.