The “definitely/probably/maybe” designation is a good one.  This was mentioned in one of the questions raised in class, but you put it a little better.  I like how one could use it to firm up plan details.  Will add that for sure!

Reputations for locations…would definitely love that.  Great idea!  I’d been thinking that I wish there were a way to rate one’s night based on the location.  Like, had a great time there, this was the crazy stuff I saw happen there, would go there again.

The posts I was thinking would be as customizable as I could figure out how to code for.  Maybe make it either public, or add individuals.  I’d have to work on it longer to make groups of people (like Google+’s circles).  But it should definitely have this eventually.

An algorithm for likelihood of a good time…you hit the ultimate endpoint of it right on the head!  I want to figure out (and reward) the most promising events, and quantify whether it was valid or not.  The “predictive badges”?  Brilliant.  That’d be the most interesting thing to code, I’ll get on it.

Great suggestions, thanks!

So would you only rate reliability for the originator or for everyone who responds?  If the originator is flaky, but you have a few solids scheduled to show up, it would still be a good chance at good time.  

Have you thought about giving the user an option on how likely they are to show up?  Something along the lines of definitely/probably/maybe. 

What about reputations for the locations?  Users doing their after-action review could rate not only the originator, but the location. 

Would the posts be open to everyone or would their be some sort of social circles?  For example, an originator could limit the post to his immediate circle of friends or expand it to plus one (friend of a friend), plus two (friend of a friend of a friend), etc.  

If you did have all that data, have you thought about some sort of algorithm to predict the likelihood of a good time.  Based on the reputation of the likely participants, the location, and how well the event fit a user’s profile, it could decide how well a fit the event is for a user.  One way to rate it would be a percentage “likelihood of a good time”.  Scores that met a certain threshold could notify the user of the event via text/email/twitter/(whatever).  Alternatively (or additionally), you could use the data to score events with predictive badges.  Some possibilities might be “bring cab fare, you’re getting drunk” or “likely sausage fest”.