EmotionML 1.0

No kidding. The new standards shape how human emotions are encoded in machine language.

Make a guess on possible applications. We can embed these “smilies” into the text as a logical structure that can be analyzed. It can also be embedded as metadata in videos and audio clips. Huge databases can be collected that show what kind of words and sounds correlate with which emotions.

Imagine a web page:

Enter your sentence: “I hate you!”
Most probable emotion: Anger (92%)

People in some call centers are mostly dealing with angry and frustrated clients, and most of their job relies on empathy. Why should they bother? Or remember that robot from the bank that called your telephone and made you angry. It might realize its mistake some day.

I hate you!

Empathy-capable machines.

And here is a very appropriate and machine readable response to emotionML by a blogger.

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