If the Internet were a royal bloodline, it’d make for one great chapter in a history book. Way back when content was king, the merit alone of an essay, video, or song was enough to warrant its success. As the months passed, however, and the amount of great material online skyrocketed exponentially, content wasn’t enough– great material needed great conversation surrounding it to ensure it truly stood out.
The evolution hasn’t stopped there, though: with time, more and more services have emerged to provide unique ways for Internet users to be creative. To help cope with the myriads of similar existing services, aggregation emerged as a method of tying one’s individual content and conversations together into one coherent bundle.
Yet the Web continues to grow. As more content and conversation is aggregated, aggregation services have even arisen to sort out the aggregates, resulting in an almost overwhelming firehose of social media noise. We need an innovator– fast– to keep us from drowning in information that is extraneous, duplicate, meaningless, or offensive.
Fortunately for the Internet, we have that innovator: FriendFeed. This new-age service has revealed to us the true ‘fourth generation’ of social media value: filtering.
How does FriendFeed filter?
FriendFeed functions by aggregating a whopping 43 services, including unique-to-FriendFeed messages, into a user’s profile. This raw collection of data is enormous and all-encompassing, including Twitter updates, Diggs, recently-uploaded Flickr photos, and latest Disqus comments, just to name a few. Multiply this enormous amount of material by ten or fifteen friends and things quickly spiral out of control. If FriendFeed were a mere aggregator and stopped here, it would be an enormous failure.
Luckily for us, it doesn’t. FriendFeed provides its users with not one but four methods of filtering to ensure individuals get content that’s interesting for them. Here’s the breakdown:
- Other-based filtering. Through use of the “best of” feature, FriendFeed can show an interested individual what’s been hot over the last day, week, or month. This is a quick and effective way to parse what others have already discovered, much like reading the front page of Digg.
- User-based filtering. If a user finds a certain service unrewarding, such as Brightkite location updates or Last.fm listens, it’s only a matter of clicks to eliminate the unwanted material. This provides a way for an individual to limit incoming data to services he or she frequents or is otherwise in better touch with. (See the power of the “hide” function in Louis Gray’s great FriendFeed Tips series.)
- Search. FriendFeed’s master-crafted search engine is enormously powerful. If a user knows what he or she’s looking for, it’s only a matter of keystrokes to immediately hone in on the topic of interest.
- Third-party accessibility. FriendFeed doesn’t keep all its material to itself, but rather provides industry-standard methods of accessing information via API, many RSS options, and more. This can be used for all manner of novel features, such as Duncan Riley’s innovative QMEME.
It’s these four filtering features that make FriendFeed so groundbreakingly unique, and I haven’t even gotten into the Rooms feature (perhaps more on this later).
The future is filtering
I’ll be the first person to admit that I don’t know how to use FriendFeed to its full potential. It’s still overwhelming, I’m still working on figuring out the etiquette, and it’s still unbalanced by the weblebrities that carry so much clout on other sites. Even though I’m a mere student of FriendFeed academy, though, I’m still able to realize that FriendFeed is extremely close to hitting the next big thing, if it hasn’t already.
Thoughts?
If you enjoyed this article, why don’t you add me as a friend on FriendFeed?
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Tagged as:
aggregation,
content,
conversation,
duncan riley,
filtering,
friendfeed,
louis gray,
QMEME
Filtering: Why FriendFeed is taking the web to the next level
by Andy DeSoto on July 28, 2008
The evolution hasn’t stopped there, though: with time, more and more services have emerged to provide unique ways for Internet users to be creative. To help cope with the myriads of similar existing services, aggregation emerged as a method of tying one’s individual content and conversations together into one coherent bundle.
Yet the Web continues to grow. As more content and conversation is aggregated, aggregation services have even arisen to sort out the aggregates, resulting in an almost overwhelming firehose of social media noise. We need an innovator– fast– to keep us from drowning in information that is extraneous, duplicate, meaningless, or offensive.
Fortunately for the Internet, we have that innovator: FriendFeed. This new-age service has revealed to us the true ‘fourth generation’ of social media value: filtering.
How does FriendFeed filter?
FriendFeed functions by aggregating a whopping 43 services, including unique-to-FriendFeed messages, into a user’s profile. This raw collection of data is enormous and all-encompassing, including Twitter updates, Diggs, recently-uploaded Flickr photos, and latest Disqus comments, just to name a few. Multiply this enormous amount of material by ten or fifteen friends and things quickly spiral out of control. If FriendFeed were a mere aggregator and stopped here, it would be an enormous failure.
Luckily for us, it doesn’t. FriendFeed provides its users with not one but four methods of filtering to ensure individuals get content that’s interesting for them. Here’s the breakdown:
It’s these four filtering features that make FriendFeed so groundbreakingly unique, and I haven’t even gotten into the Rooms feature (perhaps more on this later).
The future is filtering
I’ll be the first person to admit that I don’t know how to use FriendFeed to its full potential. It’s still overwhelming, I’m still working on figuring out the etiquette, and it’s still unbalanced by the weblebrities that carry so much clout on other sites. Even though I’m a mere student of FriendFeed academy, though, I’m still able to realize that FriendFeed is extremely close to hitting the next big thing, if it hasn’t already.
Thoughts?
If you enjoyed this article, why don’t you add me as a friend on FriendFeed?
Tagged as: aggregation, content, conversation, duncan riley, filtering, friendfeed, louis gray, QMEME