Lifestreaming Services Need Better Filtering Mechanisms

Finding ways to limit the firehose of information has become a common theme lately. I recently read this interesting post on TechCrunch highlighting the need to filter the noise. Then I read on Mashable about how Twitter can be such a time sink. Sarah Perez then goes into more detail stating that Real People Don’t Have Time for Social Media.

For me it has gotten to the point where I can’t really effectively keep track of all the people I’m following on Twitter as well as several other social & Lifestreaming services. The other day I stated that Twitter really needs to add a feature allowing us to put followers into groups for filtering. Loic Le Meur sent out a tweet stating that he was planning on creating a separate Twitter account just to follow his top friends before someone reminded him he’s got this great new Twitter client he may be able to use for filtering. I still think that the functionality needs to be added on the Twitter platform and accessible through the API for that to be effective or else you will have 3rd party apps using their own external implementation schemes which won’t be as elegant a solution or transferable for that matter.

There have been several services released that are now attacking this issue for RSS readers & aggregators using interesting methods to identify and increase visibility of the “good” stuff. They’re using algorithms that take into account trackbacks, comments, Google reader share volume, and other data points to show items that are popular.

FriendFeed bubbles up stream items based on comments and likes. Great if all of your friends are on that service, but I would want to factor the data on the source services to act as indicators for items I should view. For instance Flickr could provide data for images on times viewed, favorited, commented on, and external referrers as methods to increase importance of a stream item.

I have other thoughts on this as well as methods to filter Twitter but I won’t go into detail for fear of lulling you to sleep. I’ll try to take the time to collect these thoughts better in a future post.

7 thoughts on “Lifestreaming Services Need Better Filtering Mechanisms”

  1. Mark,

    I’m really glad you brought up this point because it’s something I’ve been thinking long and hard about. At MyBlogLog we’ve been pulling the tags off of everything coming and are using those tags as a vector on which to sort what’s coming across the transom.

    We pull together updates based on these tags into “topic” pages such as the lifestream page you wrote about earlier:

    The New with My World page will feature a mixed feed of all the updates from any member that matches either Topics that you follow or Tags that you have applied to your own profile.

    We’re still in the early stages here – we’ll add ranking mechanisms that will help bubble up to the top updates that are more relevant to you based on what we know about you and your friends. We also need to do a better job of highlighting the relationship between what you see on New with Me and your Tag cloud on your profile. The goal is to make your New with My World an effective filter and hopefully a place to visit for further discovery.


    Product Guy, MyBlogLog

  2. I started LiFE2Front’s LiFE-Line project (lifestream based profile) more than one year ago… And I’m surprised nobody copied my features : filter by entries type* and related tags. And I’m going to deploy new “instant” search engine.

    (*) why filter by services like FriendFeed ? Isn’t most usefull to get every bookmarks from any services ?

    And I think most important is to separate our content (blog, photos, videos) between our bits of activity (microblog, listen song, used softwares, voted/liked items, etc)… In fact, my profiles manage 2 lifestreams per users.

    And the last but the best, I built process to detect redundant entries (ex: bookmarks or microblog updates).

    My next product ; Seek-LiNE friendstream service will use same features (type/tag filters and un-redundant process)… And 2 friendstreams per users networks.

    Today, I think I’m alone who spent long time to study users usages, desires, and needs. I made the choice to build perfect platform than open firstly… Wait’n’see ;o) .oO(Rome’s empire hadn’t built while one day)

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