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NoiseRiver is 1 month old! And it goes Beta!July 26

Oh yes!

One whole month of delightful developping. I remember the first day it was released and the plug that Louis Gray and many people gave it! Phew! It's simply phantastik!

What started as a little challenge after some discussions I've had with some people on FriendFeed like Robert Scoble, Louis Gray, Duncan Riley and many others, suddenly became a very nice app with so many features that are not even present in FriendFeed itself! Sorry folks, but I really feel proud :)

Not only proud but so much grateful for many people that helped me by issues reports, ideas, fixes, opinions and tons of nice and kind words everyday. And that's the real magic of this experience! I was so encouraged by friends on FriendFeed that I was able to deliver at least one (if not two) features daily! So I'd like to say a BIG, no, no, a HUGE thank you!

Thanks to them, NoiseRiver is humbly the most complete FriendFeed App out there! It includes almost every possible feature that the main FriendFeed's UI includes plus a dozen of new ones.

People don't believe that NoiseRiver is "alpha", and some even wonder what

Explaining the new "Watch" feature of NoiseRiver and How it will cure the "Comments Clusters" diseaseJuly 26

Hello folks,

Today, I'd like to tell you about one of latest features of NoiseRiver that has been released since my last update.

Last Monday, Robert Scoble started an intersting discussion about how comments clusters maybe confusing and redundant sometimes on FriendFeed. For example, we start a discussion about the latest Louis Gray's blob post, because we saw that URL shared on Google Reader by someone, and then someone else shares the same thing on del.icio.us, and so on... we may end up with dozens of comments clusters on the same subject. This is "comments fragmentation" inside FriendFeed itself.

What would be intersting is the ability to gather all the comments clusters about the same subject, group them in one place and see how people react, and have a better opinion, be more informed etc.

This, in fact, is the mission of the "watch feature" of NoiseRiver! You want t

NoiseRiver: 6 days later, 8 new features!July 16

Hi folks!

I'm crazy when it comes to programming! But, I must admit that I'm really lazy and not that good when it comes to writing blog posts --while I really should do it. In fact many features were added to NoiseRiver since my precendent post (a week ago) and I think that it's time to give people some updates here on the blog --even if I was posting Live Dev' Updates in FriendFeed.

So here we go:

Feature 1: Hide by URL

Say you've seen a blog post (or any url) posted on FriendFeed, and that you're done with it. And you want to hide any further posts about the same URL. FriendFeed doesn't offer this kind of hiding, so I added it to NoiseRiver. Now you can see a URL only once if you want.

Feature 2: Little reply icon

NoiseRiver: Two weeks later, many features addedJuly 10

Howdy! 

Phew! What an exciting experience! Two weeks of happy coding on NoiseRiver and many features added. What's more joyful about this was the "watch me cooking" style of coding I've adopted lately. In fact, there was a happy crowd in the NoiseRiver's Room reporting bugs, suggesting features and improvements. And me sending "Live Dev' Updates" from time to time and having feedback instantly!

So, here we are, two weeks later and a bunch of new features like:

• Integrating rooms to NoiseRiver (with the ability to show rooms contents, and share in rooms)
• Hiding and deleting entries: NoiseRiver was the first FriendFeed App to integrate these features.
• Reshare entries
• Added comments timestamps (even before FriendFeed did ;-) )
• Added a nice tooltip that displays a user's information (including an expanding list of his rooms)
• Added likely comment's replies highlighting (comments that include one's nick or name)
• Added Social proximity to the tooltip that shows how

Wait, wait, that was just ONE feature of NoiseRiver! Here's "Smart Social Connexions"July 1

What a stressfull day! I worked on some NoiseRiver's backend improvement and I'm strating to build with only javascript and JSON some new UI elements. But the hardest of it all, was the loss of the domain name and then the re-registring of it again... Story discussed on Friendfeed --of course :)

Anyway, today I wanted to talk about the one feature that, when implemented, will make all the friendfeed gals want to mary me! True! :)

Many people are complaining about the fact that almost all social websites recommand allways the same people as friends (understand A-listers: Scoble, Loic, Arrington...). They're right, being popular doesn't mean that we share intersts! Period.

So here's the idea: Imagine, that given Paul's Interests and neighborhood settings, we may compute and find the most resembling people, those who share the maximum of these with Paul. The more people share these things with Paul, the more they're likely to be/become friends. Isn't it?