Is FollowFriday even Valuable?

I’ve been tracking FollowFriday for a while now and using justSignal to power FollowFridays.com – and today it really, really looked like FollowFriday had jumped the shark.

Here’s the thing. If you compose your FollowFriday tweets like:

#followfriday @joe @mary @steve @beth

You really aren’t adding any value to FollowFriday – as a matter of fact I’d argue you are just creating noise. Here is why. The simple reality is that I only follow about 10 or 15 people who I know well enough, trust enough, and have enough of a complete relationship that I would simply follow someone they told me to. And odds are I’ve been following those people for some time now and follow nearly everyone they would recommend.

So your @username missle for FollowFriday has no effect on me. I’m not following them… my guess is very few others will either.

But, if you compose your FollowFriday tweet like:

#followfriday Follow @micah because he came up with this and @strebel because he has mad design skills

I can determine if I want to follow those people based on WHY you follow them… not just because you said so. Even more powerful is the ability to head over to FollowFridays.com and enter a filter on the Tweet Stream (click on “filter this content”) for “cool” or “design” or whatever it is you are looking for and see JUST the FollowFriday Tweets with that word in them.

Today, based on what I was seeing and hearing it appeared that the majority of the tweets for FollowFriday looked like the first example. If that were the case – I’d have to say FollowFriday had outlived it’s usefulness.

Conveniently – because we us justSignal to track FollowFriday – we have access to each and every tweet sent about FollowFriday. So I decided to rely on data… and here it is:

tweets-of-value2

NOTE: Tweets of Value is defined as any tweet that does not contain all @names and hash tags. Raw hour by hour data posted after the jump.

As you can see – while a significant number of the tweets (about 20% overall) were just hash tags and @names the vast majority actually contained useful words (hopefully) describing why we should follow the people being recommended.

I’ll grant you that we did not perform any kind of semantic analysis on these tweets trying to determine intent to state why someone should be followed, but I’m still pleasantly surprised that a consistent 80% of the tweets were not all @names and hash tags.

Make sure you tell everyone – only do FollowFriday recommendations with reasons… it is much more effective and keeps FollowFriday valuable.

One other thing I’ll take a moment to mention (shameless plug) – How cool is it that you can think of something interesting to discover from Social Media data and immediately be able to go answer that question? That is part of the power of justSignal… check it out.

Continue reading “Is FollowFriday even Valuable?”

Twitter, @replies and Multicasting

Twitter made a change to how @ replies are handled yesterday and the response has been, well, loud. Essentially you used to be able to see @ replies to everyone you followed, even if you didn’t follow the sender. Under Twitter’s new rules you only get to see @ replies to people you follow IF you follow the sender.

To many this may seem like a trivial change, but to those who use Twitter to discover interesting people… it is a very big deal. There has been rampant speculation (ignited, near as I can tell, by this post from Jesse Stay of SocialToo) that this change “kills” Follow Friday.

I’m including my comment on Jesse’s post here:

Ok… just to clear this one up. I checked (as you know I use justSignal to track Follow Friday for http://followfridays.com).

I have every Follow Friday tweet from 4/13 – 5/13 (last 30 days). There are a total of 771,244 Tweets. Of those 220,166 BEGIN with @username. That is 28.5% of the Tweets.

So definitely NOT most… but a very significant percentage.

Also, we’ve added User Filters to justSignal on FollowFridays. What does that mean? You can filter the total Follow Friday Tweet Stream by what it is about people you want to discover. Want to find PR folks to follow… add a User Filter for PR…

Follow Friday is most certainly NOT dead.

The short version of my take on this is that there are much, much better ways to find interesting people to follow than to rely on the people you follow to tell you about them. Don’t get me wrong, I believe in the power of recommendations, but I also believe in the power of context.

You see, my fictional Twitter Friend Joe is really, really into late 13th century birth control. I – for whatever it is worth – find his updates about walrus skin condoms entertaining. Beyond that Joe and I don’t have much in common. There is nothing atypical about this Twitter relationship… in fact, if I had to bet with my own money I would guess that 90% of Twitter relationships are pretty similar to this. So, Joe’s Follow Friday recommendations are only valuable to me in a very, very narrow window of my interests… so if I don’t see them all am I really missing anything?

What I really want is to see the recommendations from the 10% of the people I follow with whom I have a much broader affinity AND people recommending others because they are really smart about (CONTEXT). Whatever my context of interest happens to be right now.

That is why we’ve added User Filters to the justSignal Tracker on FollowFridays to allow you to filter the live Twitter Stream for your context, your 10%, or whatever else makes Follow Friday work for you. That is what we call – Getting Signal.

Multicasting & @ Replies:

UPDATE: 05/13/2009 @ 4:10PM Pacific Time

I blew it… the below examples misrepresent what the @ reply option did. I’m not going to redact it or change it… because:

  1. I blew it… and that happens and is ok with me.
  2. The example of Tweet distribution as it relates to a multicast system vs. a non-multicast system is still 100% relevant and correct.

END UPDATE

Biz made an update to the Twitter blog letting us know that the change to the @ reply system wasn’t really about user confusion – but a technical issue. This is a reason that actually makes sense. It makes sense for one simple reason – the “web” and Twitter were not built to efficiently implement multicasting. The problem with these @ replies is they create a burst of Tweet traffic… why?

If you create a normal Follow Friday tweet like:

#followfriday @joe @mary @steve @mike @larry @meg @biz @wally

That tweet will be sent to joe, mary, steve, mike, larry, meg, biz and wally. Let’s say each of them are followed by 400 people. And let’s say 60% of those people have “show me all replies to those I follow” checked.

This tweet will be sent 1,928 times:

  • 8 – The original 8
  • 240 – Joe’s followers who’ve checked show me all replies
  • 240 – Mary’s followers who’ve checked show me all replies
  • 240 – Steve’s followers who’ve checked show me all replies
  • 240 – Mike’s followers who’ve checked show me all replies
  • 240 – Larry’s followers who’ve checked show me all replies
  • 240 – Meg’s followers who’ve checked show me all replies
  • 240 – Biz’s followers who’ve checked show me all replies
  • 240 – Wally’s followers who’ve checked show me all replies

Now lets say we create the following Follow Friday tweet:

#followfriday @scoblizer @mashable @aplusk @oprah @cnnbrk

Again, let’s round things off and say each of these people are followed by 700,000 each and 60% have “show me all replies to those I follow” checked.

This tweet will be sent 2,100,005 times:

  • 5 – The original 5
  • 420,o0- – Scoble’s followers who’ve checked show me all replies
  • 420,000 – Mashable’s followers who’ve checked show me all replies
  • 420,000 – AplusK’s followers who’ve checked show me all replies
  • 420,000 – Oprah’s followers who’ve checked show me all replies
  • 420,000 – CNNBRK’s followers who’ve checked show me all replies

YIKES!!! Now imagine that tweet getting re-tweeted a couple hundred times. This is both why Twitter (I’m speculating here but with a high degree of confidence) “edited” trending topics to exclude Follow Friday AND why the @ reply change was made.

Why Multicast Matters:

Today Twitter (because they don’t implement efficient multicasting and instead rely on publish/subscribe architectures) has to effectively send each of those 2,100,005 tweets serially, one at a time. This consumes massive amounts of computing resources.

Multicast would allow them to send it once to many destinations – thereby removing that bottleneck from their scalability and tweet processing systems.

Those of you who are familiar with large scale real-time communications systems (i.e., VoIP) will immediately recognize this problem – it was central to creating a large scale VoIP service platform in the late 1990’s. The VoIP community resolved it (not without much effort) and now a very small system can efficiently multicast hundreds of millions of status updates/changes per hour.

I totaly buy Twitter pulling @ replies due to technical issues – as exposed by Follow Friday combined with celebrity adoption and massive follower counts. But if you are going to be the real-time web backbone disabling useful things because they create too much load instead of implementing a more efficient architecture isn’t the right answer.

justSignal Upgrades, or My Lame Attempt to Explain Ignoring My Blog

I’ve gone through another one of those spells where I just didn’t write anything here – and to say I’ve been busy isn’t enough – hell I’m always busy.

I also can’t claim lack of interesting content – I could write six really compelling pieces on ASU Startup Weekend alone.

So we’ll just agree that my energy for writing posts took a bit of a vacation… but now I’m back.

Before I get back to my regular banality I need to get a bunch of housekeeping taken care of, so this post will catch you up on the justSignal updates, upgrades and new features.

Details after the jump…

Continue reading “justSignal Upgrades, or My Lame Attempt to Explain Ignoring My Blog”

There Are Practical Limitations on Real-Time

No one is a bigger fan of real-time than I am. I’ve been working on real-time communications for 10 years, and I intend to continue to work in that space for the foreseeable future. That being said, let me be clear about one thing: There are practical limitations on real-time.

FriendFeed launched their new UI today in beta (check it out here). I am a huge fan of FriendFeed – and have been for a while now. They are doing more to advance the real-time web and social aggregation than any other service. But…

The new user interface (UI) leaves me with a single takeaway. This beta clearly demonstrates the practical limitations of real-time. If we begin with the end in mind, and clearly say that real-time exists as an enabler of:

  1. Communication
  2. Information Discovery

we quickly see that at some point real-time becomes a barrier to both.

New FriendFeed User Interface
New FriendFeed User Interface

I follow roughly 400 people on FriendFeed – which isn’t a particularly big number – and with the new full real-time user interface both communication and information discovery become all but impossible.

People are going to tell you “you’ll get used to it” – I actually saw one user compare it to flying a plane – information overload at first, but once you do it a while it starts to become less overwhelming. That may be true, but communication and information discovery shouldn’t be like flying a plane; which is a decidedly life or death experience. It should be streamlined and optimized to take advantage of the limited attention of the user. As importantly it should allow the user to take control of the experience and allocate their attention as they see fit – dynamically – as their attention allows.

And this is exactly where the new FriendFeed user interface breaks down. It requires 100% of you attention, 100% of your mental cycles – and it is still almost impossible to actually accomplish your goal; communication or information discovery.

FriendFeed has the building blocks in place to better manage your limited attention, but they are tangential to the central user experience and lack critical features. Filters and lists can solve the problem of limited attention, but they must be at least as functional as the current user interface – including the ability to post and follow the information in real time.

This puts the user in control of how they allocate their scarce attention – too much to pay attention to, tighten up the filter – not enough action, broaden the filter and get more.

At justSignal we are solving these problems as a platform for other companies, brands, or organizations to leverage in their content. FriendFeed needs to keep their eye on the ball, because they are solving it (IMHO) for the individual consumer.

The “ball” is enabling communcation and information discovery… that should be getting 100% of our attention.

Another justSignal upgrade. Twitter real-time upgrade.

We had a list of items we wanted improved and added to the justSignal Twitter real-time widget. And since I have no ability to procrastinate we are launching those changes over the weekend. Here is a rundown of the changes:

  • Allow for variable length hash tags to be inserted in the tweets (used to be fixed at 6 characters).
  • @names are now links.
  • Added HTML elements for easier customization via CSS.
  • Delete old tweets when there are more than 350 in the widget.
  • Added date on tweet time.
  • Added “logged in as” and a Logout button.
  • Added the ability to re-tweet directly from the tweet (no copy and paste, just click on RT).

Re-Tweets are a big deal. So is the capping of the number of tweets in the widget (prevents memory issues). I’m also pretty happy about the improved HTML which will allow you to customize nearly every aspect of the widget via CSS (thanks to Josh Strebel for his guidance here).

For those of you who need to see it now… here is a screen shot of the base widget (not customized).

justSignal Twitter real-time Widget
justSignal Twitter real-time Widget

We still have much, much more up our sleeve(s)… so stay tuned.

justSignal Adds More Signal

I’ve been awfully quiet for the last week or so. And there is a reason for that.
I’ve been busily working away to fulfill the vision of justSignal. It was never about (just) Twitter – it was about finding your signal wherever someone chooses to talk about it.

We launched with Twitter and the real-time widget because – frankly – Twitter has the buzz factor and because real-time is compelling. Today we are expanding beyond Twitter and the real-time, with the addition of Backtype (blog comments) and Google Blog Search. These new widgets will be added to the standard justSignal Tracker offering – with no increase in price.

These widgets have all the capabilities of the Twitter Real-Time widget:

  • Auto Updating when new data arrives
  • Fully customizable for your site via CSS
  • Dynamic search/filter terms that can be changed at any time
  • Embeddable in any site/HTML

Google Blog Search Widget:
http://justsignal.com/widgets/brianroyblog/embed-blogsearch.js Backtype Blog Search Widget: http://justsignal.com/widgets/brianroyblog/embed-backtype.js

But wait there’s more!!! And it isn’t a shamwow.

We’ve also added a search widget. The search widget searches within the Tweets we’ve collected based on your filter. The more (default is 2 hours – with options up to 90 days) history you keep the more useful this search becomes. To demonstrate this search capability we’ve launched Great On Twitter. Great on Twitter collects everything said on Twitter when someone thinks something is great, shows those tweets in real time and allows you to search for things that interest you.

For fun try searching for iPhone (note the number of matching tweets), then search for Blackberry. Another fun example is TweetDeck/Twhirl.

We aren’t done… not even close. So stay tuned for more updates.

Follow Friday – March 6th, 2009 – Tracking the Meme

Well this appears to be my new Saturday morning ritual. Pulling together data from Follow Friday for your viewing pleasure.

I want to thank Mashable and Micah for the post on Mashable yesterday featuring a screenshot of the justSignal Follow Friday Tracker.

Well lets get on with it, shall we?

There were a total of 43,481 Tweets (midnight to midnight Pacific Time).

Here is a chart showing the number of Tweets per hour (again time is Pacific).

200903070933.jpg

The peak hour was 9-10am Pacific with 4,450 Tweets.

Perhaps my favorite fact from this week. 43,728 unique Twitter users were recommended.

Starting next week I’ll be providing week over week trending data… which should be really interesting. Since my data for last week is incomplete we really can not judge growth, but my best guess is that the Tweet volume about doubled.

For specifics about which users received how many recommendations and from who, head over to TopFollowFriday.

Two more things this week. First, I’m making the entire days worth of data available via an XML file. You can download it here. Be warned, it is a 22MB file. The format is described here.

Second, Jeremiah Owyang thought (and I agreed) that Mashable got many of their Follow Friday recommendations via the Re-Tweet of the post Micah wrote. Turns out (near as I can tell based on my analysis of the data) – not so. There were only 65 Re-Tweets for Mashable which would have been counted for Follow Friday.

tw-temp-jowyang.tiff

After the jump you can see those tweets for yourself.

Continue reading “Follow Friday – March 6th, 2009 – Tracking the Meme”