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Signal to Noise: Twitter, Blogging, and Your Other Crap

Signal to Noise Filter

One of my favorite authors, Seth Godin, recently touched upon the subject of signal to noise in social media and the web in general. It’s interesting to me that his perspective comes at such a fortuitous time as this. Literally, the day a few of us will be getting together to discuss the very issue.

Signal to noise ratio. It’s the term used by radio operators to describe the amount of quality sounds they’re able to hear over the static. Blogs and Twitter are perfect examples of this. There are zillions of blogs out there now, and thousands more being created every day. Are any of them valuable? Twitter asks “what are you doing” and I have to admit I put much more than what I’m doing into that little box. In fact, Lisa Brewster and David Horn have dubbed the problem infamously “Nate limiting” (as opposed to “rate limiting”). As honored as I am to be a part of the meme, I also want to find a solution to the issue.

There’s quite a few people now talking about this issue. What we need now is not aggregation. That just puts all the noise in one place. Although, aggregation might be a necessary step to see that it doesn’t work first.

We’ve gone from a top-down approach to publishing content into the era of “user” contributed content (don’t get me started on the word “user”). Now we can publish anytime, anywhere, on almost any consumable media.

So, what happens next? AllTop, Guy Kawasaki’s creation.

AllTop cracks me up, actually. If you don’t remember the original Yahoo!, you probably don’t understand why. Yahoo! started out by being a directory of organized interesting and relevant (“top”?) websites. Then Google came along and kicked their ass because we wanted more content than just a directory. Now we’ve got too much content and we just want the “best”. See the pendulum swinging again? It’ll go back and forth like this until someone solves the issue with a filter of some sort.

Enter “Nate limiting” and the content, priority, and “friend” filter. There will be a solution, it just might take some work on the human’s part to tweak it right.

The only thing that’s come close so far has been Facebook’s feed preferences (screenshot below).

Facebook signal to noise filter

We need more than a closed filter though. What do you think the solution is? Would the general population even use a solution like this?