What do you do if you have subscribed to a bunch of blogs and feeds, but now find that you are inundated with an avalanche of information, only some of which is really critical? How can you sort and filter this information and add some relevancy?
Here are three techniques to consider:
- Automated Manual Filters – online tools that help you filter blog posts by keywords
- Aggregated Global Social Filters – online tools that rank posts in a blog by how the global population treats that post
- Human Filters – online social tools that let you subscribe to posts filtered by friends
These techniques all offer a different type of filtering. Choose whichever suits your needs.
Automated Manual Filters
An obvious technique in adding relevancy is to filter out the irrelevant based on a keyword search. In other words, match each post within a feed against some criteria, and if there’s a match, either keep or remove that post.
I sometimes use Feed Rinse to do this, though there are other filters on the market such as mySyndicaat and more. You can even use Yahoo Pipes. So what does Feed Rinse do? (Feed Rinse is the most intuitive for the everyday blog reader, though I’ve had a few problems with Atom feeds.)
Essentially, it allows you to import your feeds (individually, or via OPML), apply filters to the feeds (only allow a post if it contains the words “Stephen Fry”, or only allow a post if the title contains “Wilde” and so on), and it then spits out a new, filtered feed that you have to subscribe to. This new feed will only contain items that match your filters.
This is an effective way to cut down on the extraneous material, and Feed Rinse tries to make it easy by allowing you to import en masse, apply filters to individual feeds, aggregate individual feeds into channels, apply filters to channels and so on. In other words, I could grab several feeds from various news organizations, add them to a channel, and apply a filter to the channel. The result would be a single feed that only contains items from across all the organizations that match the filter.
Aggregated Global Social Filters
A very different way to look at information coming from a feed is to filter it by ranking the posts within the feed and only viewing those posts that are “good enough”. In other words, instead of consuming the entire feed, you can simply subscribe to a percentage of those posts.
For this kind of filtering, I use aideRSS. aideRSS uses what I call a global social filter – it looks at how the world is reacting to posts within a feed. For each post, it examines at least the following: its digg rating, how many folk tweeted the post, its del.icio.us ranking and how many comments were left on the post. You can then subscribe to a percentage of these posts by subscribing to the “good, great, best or top 20″ posts within that feed.
In other words, aideRSS filters the posts within a feed based on some ranking, and then presents you with a new feed that you have to subscribe to (that contains only those relevant items).
It’s a pretty nifty service, and though you may not want to use this kind of filtering everywhere, it’s an awesome tool to have.
Human Filters
A few blog readers such as Google Reader let you apply the nous of your local social circle to filter posts. In this form of filtering, you let your friends tag or flag or “mark as shared” items that they read in blog posts, and you subscribe to this shared feed.
It’s not ideal: there’s no way to rate an item based on multiple people, nor is there a way to share an item to a “shared feed” to which multiple people can post.
Nevertheless, this can be useful if you have a domain expert reading the posts anyway. He’ll be filtering, and if there’s prior agreement as to what he’s sharing and why, this can be very useful.
See the “Settings/Tags” menu option to set up or change sharing options in Google Reader.
(You could get into a more complicated scenario where you feed multiple human filters through a feed combiner, but that seems a little OTT. What we really want is a social aggregator.)
Postscript
I wish Google Reader or NetNewsWire supported additional features to help readers filter posts. For example, I can’t highlight blog posts that meet certain criteria, which I thought would have been a basic need. In NetNewsWire I can create a “smart feed”, but that’s not quite the same thing. Neither can I automatically filter out duplicates, which is an absolute drag, especially as I subscribe to feeds as well as aggregations of feeds.
There’s still a long way to go in filtering the blog avalanche, and I’ve seen surprisingly few client side features to help. Hopefully these three techniques will help you out while our blog reader clients mature.
Technorati Tags:
blogging, aiderss,
feed rinse, google reader, netnewswire
