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How to Mess with Bloggers’ Heads Using FriendFeed Lists

Steven Hodson, blogger extraordinaire at Winextra, posted this on FriendFeed:

“Okay this is cool .. someone has setup a Curmudgeons list and I’m apparently part of the list ROFL”

Inside the blue highlight box, you can see a referring URL that someone used to get to his blog:

http://beta.friendfeed.com/list/curmudgeons

That is someone’s List on FriendFeed. They’re put him into a List called “Curmudgeons”.

You can customize your own referral URLs with FriendFeed Lists. The tags you use for a blogger will be seen by that blogger as they look at their referral traffic.

Oh the possibilities…

  • beta.friendfeed.com/list/brilliant
  • beta.friendfeed.com/list/dumbass
  • beta.friendfeed.com/list/stop-blogging-about-twitter
  • beta.friendfeed.com/list/free-trial-of-viagra
  • beta.friendfeed.com/list/can-you-come-upstairs-for-dinner-please

You can create a List, click through on it, and the blogger will see your special anonymous message. Lists are easy to create and delete, meaning you can do it as much as you want.

So have fun with your favorite bloggers – send ’em those subtle messages with the tags you use in your Lists.

But you don’t have to do that with me…uh…we’re cool, right?

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22How+to+Mess+with+Bloggers%E2%80%99+Heads+Using+FriendFeed+Lists%22&public=1

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Filtering FriendFeed – How Crowdsourcing Can Solve This

It would be nice to have filters on FriendFeed. For instance, it would be nice to be able to hide any post containing the word “Obama” without having to hide someone’s other stuff. Or the ability to hide any entry containing the word “ubuntu”, etc.

Thomas Hawk, FriendFeed direct post, May 1, 2008

The need for filters on FriendFeed is a recurring topic. Click here to see the numerous entries that contain the words ‘friendfeed’ and ‘filters’. Louis Gray notes the need for this in a recent post.

I want present an idea for filters that has two pieces:

  • Category filters
  • Keyword filters

The two pieces are interrelated, and crowdsourcing will be used to build out the category filters.

Let’s get to it, shall we?

Category Filters

FriendFeed already has a “Feed Preferences” page for each member. Here is where you can manage your category and keyword filters. The graphic below is mockup of this:

A. Category Filters

Various categories will be displayed, along with a link to the full list of categories. In the example, above, I say that I’d like to filter out all FriendFeed entries that relate to politics.

The value of category filtering is that it prevents you from having to manage every keyword that might relate to a category. In a recent post, I noted Dave Winer’s 38 different politics-related terms. For instance, he used the terms: Hillary, HRC, Clinton, Edwards, Obama, Rove, etc. Having the ability to automatically filter those out without having to set up keyword hides over and over would be a great benefit to many members. Particularly as FriendFeed gains traction with a flood of new members.

Now how would FriendFeed know that Hillary, Obama, HRC, etc. are part of the politics category? Keep reading.

B. Keyword Filters

Members will need the ability to see what words they have hidden. They can un-hide keywords, or add new keywords to hide directly on the Feed Preferences UI.

Keyword-Based Hides

FriendFeed currently supports hiding specific entries, plus entries from specific members and services. For instance, you can hide all Twitter updates. What is lacking is the ability to filter out entries with specific terms in them.

For instance, shown below are three tweets from Dave Winer regarding politics:

What I’d like to do is apply the Hide function to anything with ‘Harold Ickes’ or ‘Henry Waxman’. This is a mock up of that screen below:

A. Full Text of Entry Displays

The full text of the entry appears. Each word of the entry includes a link. The links are easy ways for members to populate the ‘hide terms’ input box.

B. Hide Terms Input Box

Commas separate each term.

C. Categorize the Terms to Be Hidden

As the member hides the terms, they will be asked to apply a category. The most popular categories previously applied to the keywords will be displayed. Or the member can type a category into the input box, and FriendFeed will auto-suggest different categories with each character entered.

Why do this? This is the basis of the crowdsourced solution.

Let the People Decide

People will have a much better handle on the categories that apply to a keyword than will a heavy-duty algorithm. Such human filtering is the basis of tagging.

Two elements are relevant here:

  • The need to prevent bad categories being assigned to keywords
  • The motivation to do this categorizing

Use Bayesian Stats to Prevent Bad Categories

Here’s the issue you want to avoid. Some prankster assigns the football category to the term “Paris Hilton” while hiding all entries containing her name. Suddenly, members who are filtering out football entries stop seeing their Paris Hilton updates (yes I know, horrors…).

Enter Bayesian statistics. Carl Bialik, a columnist for the Wall Street Journal, has a great column on the use of Bayesian stats for online ratings. The gist of this approach is that all items in a rating system are born with identical ratings. Their ratings only change as people vote, and it takes a sufficient number of votes to really move the rating of an item. Here’s an example of this from the WSJ column:

For instance, as noted in the column, IMDB.com doesn’t use straight averages to list the top 250 movies of all time, as voted on by its users. Instead, each movie starts out with 1,300 votes and a ranking of 6.7, which is the site’s average. That helps smooth the effects of a few intense votes; it takes a lot of votes to budge the IMDB meter up or down from 6.7

That same approach would be applied inside FriendFeed. It would take a large number of people putting a keyword into the same category before the keyword actually became “part” of that category.

Once a keyword graduates to a category, any users filtering that category won’t see entries with those keywords.

Motivation

Why would anyone bother to categorize the keywords they hide? One answer – not everyone will. But there are two drivers of members doing some keyword categorization.

First, members need to recognize that they are contributing to a system from which they are likely benefiting. If you filter any category, you will be benefiting from the work of others’ who have categorized keywords.

Second, the categorization experience has to be simple and fast. You’ve got the member right there, motivated to hide a term. Make it easy for them to channel that motivation into a simple categorization. The most popular previous categories are displayed, making it easy check them. And the auto-suggest feature can be done fairly quickly. I like how Faviki is doing it:

Faviki draws from thousands of different Wikipedia entries for this list.

Final Thoughts

One thing to consider here is that every entry coming into FriendFeed would need to be filtered for keywords. Serious processing power will be required. Fortunately, the FriendFeed guys have firsthand experience with high volumes of real-time queries for keywords at Google.

With regard to this proposal, I haven’t (yet) seen anything on the market that will provide the category tags that would help filter FriendFeed. Since it’s the members who are most in tune with what they want to filter, their common sense and motivation should be leveraged.

As FriendFeed grows, imagine new members easily managing the flow of information by simply filtering the politics category rather than having to set up an extensive list of new keywords. It would make the experience that much better for everyone.

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22Filtering+FriendFeed+-+How+Crowdsourcing+Can+Solve+This%22&public=1

FriendFeed Tags Make Your Stuff Findable

A theme I come back to repeatedly here is that FriendFeed will be a terrific platform for research and discovery. In fact, for this purpose, FriendFeed gets better the more people use it. That’s a contrast from the information overload meme that has emerged, in which too many friend updates overwhelm people.

Another way to put it: “Research” FriendFeed versus “Friends’ Updates” FriendFeed.

A good point of comparison for Research FriendFeed is Google. Google is the first stop for most people when they want to find information on something.

A key difference between FriendFeed and Google is that Google indexes all the content on each page. A Google search will go deep into a web page’s content. FriendFeed has only limited information in each update:

  • Blog or article title (blog post, del.icio.us, Google Reader, Reddit, etc.)
  • 140-character message from Twitter
  • Name of the Flickr photo
  • Etc.

This puts a lot of pressure on the title of the article to well-represent its content. Many times it does. But more often than not, the article is richer in information than the title can convey. Also, contorting your writing – including the title – to maximize search effectiveness is just a bad move. Bad for writing, bad for reading, bad for authenticity.

These two dynamics – lack of full content, incomplete information in the title – call for innovation within the FriendFeed world.

Where will that innovation be? FriendFeed comments.

Comments are free-form, and easy to add. And they’re part of the FriendFeed search index. If a good conversation erupts around an activity feed, those comments can be helpful for searches. But the conversation may not hit the mark either. And the majority of updates do not have a rich conversation around them.

As the author of a blog post, you may want to take a more active role in whether your content shows up in searches on selected terms. May I suggest tagging as an answer here?

In a comment, simply type ‘tag:’, followed by any tags you’d normally use. Using the “tag” prefix lets everyone know that it’s not a conversational comment. It’s a metadata comment.

Here’s an example. I recently wrote a post called, “Innovation Requires Conversations, Gestation, Pruning“. The article can apply to any general environment where innovation occurs. However, the focus of the post is really on employees inside companies. Internal blogs can be powerful centers for incubating innovation.

The post has a strong Enterprise 2.0 theme. Yet the title of the post doesn’t tell you that. So I went into the comments section for the FriendFeed blog post update, and added this:

tag: enterprise 2.0

Sure enough, the post now shows up in a search for ‘enterprise 2.0’. It also showed up in my RSS feed of ‘enterprise 2.0′ updates from FriendFeed.

Not everyone will bother with tags, of course. But tags are mighty useful things. If you create content and want to make sure it’s findable, tags are a good strategy to make sure it’s “findable”.

And this idea extends to adding your own tags to others’ content. You could create your own tags to associate to content you like and want to track.

And tags help others understand the context of the content.

This post may be a bit early. But it is something to think about in a future where FriendFeed is the third leg of research: Google, Wikipedia, FriendFeed.

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22FriendFeed+Tags+Make+Your+Stuff+Findable%22&who=everyone