Digg Filter, a Recommendation Engine for Digg – Interview with Founder

This is a guest post by Muhammad Saleem, a social media consultant and a top-ranked community member on multiple social news sites.

We have been hearing about an upcoming new way to discover content on
Digg for quite a while
now. The new Digg ‘recommendation engine’ will purportedly look
at your past submissions, Digging, and burying activity – and from all that recommend
other stories that you might like. This system won’t be much different
from how Reddit‘s ‘recommended’ page works, or how StumbleUpon
generally functions. While we wait for the Digg recommendation engine,
which is perpetually ‘coming soon’, one enterprising Digg user has
taken the initiative and built one himself. After putting in 200 hours of his own time, Dmytro Mulyava has
come up with Digg Filter, an API based Digg story recommender.

We had the chance to talk to Dmytro and ask him some questions
about Digg Filter.

Before we begin, can you tell our
readers a little more about yourself. Who are you, what you do, and
how you got involved with Digg?

Sure, I am student at a business school here in Toronto and I am
really passionate about the Internet and the things that it allows
people to do around the world. I first heard about Digg through an
article in Business Week in August of 2006 and thought to myself “Hey,
that’s a pretty neat idea!”. Since then I have found Digg to be a
great source for things that wouldn’t be broadcasted by other media
sources.

How active are you on Digg and what is
your opinion on how the site has evolved since when you first joined
and started participating in late 2006?

I lurk Digg a few hours a week and Digg some stories here and there,
based on the content I find to be interesting. I am certainly not a
power user – I never submit stories because I know my stuff is never
going to make it to the front page. I love the comments – the top 5
(sorted by Diggs) for any story can be downright hilarious! Digg has
been is growing at a very fast pace. While some feel that this is
“bad” because content quality is declining as the user base expands, I
haven’t actually noticed this.

Digg has many different visualizations
and ways to discover new content. Which would you say is your favorite?

I like Digg Spy. It
is simple yet useful. There is something addicting about watching the
stories scroll through and see how users are interacting with them
(submitting, Digging, burying, and commenting).

But even given all these tools, you
felt that there was something missing in the features Digg has and you
decided to make a service of your own called Digg Filter. Tell us a
little about this service and how you envision it being used.

The idea behind Digg Filter is very simple. I want to help people
discover content based on their past preferences. Digg Filter looks at
users’ Digging patterns and tries to “guess” what fresh content they
will enjoy.

There are many, many stories submitted to Digg on a daily basis, more
than anyone could ever sift through. Most of these stories never make
it to the front page – and as such are undiscovered by the majority of
the people. Hopefully the tool will help users find these “hidden
gems‚Äù that the majority of the community moderated so they couldn’t be
promoted, but may be of interest to you.

I see the service being used by Diggers who are in a rush to find “the
stories that matter” without flipping through many pages in the
“Upcoming” section or relying completely on the front page of Digg.

Could you give us an idea of how these
results are formulated? What specific data are you taking into
account?

Digg Filter looks at pretty much everything. (grin)

There are a couple of things that
worry me about the site though. First of all, you use Digg in the url
and the name of your site, something that could get you a cease and
desist from Digg, and second, Kevin Rose has already mentioned that an
official Digg recommendation engine is coming soon. What impact do you
think these two things may have on your service?

Those are two very valid concerns! If the folks at Digg want me to
shut down the service, so be it. It (Digg.com) is their site and their
trademark. I am obviously using their API to piece this together. They
can unplug me at any minute and I understand that and hope that they
will be a little more reasonable about it.

As far as the official Digg recommendation engine is concerned, I
started work on my recommendation algorithm before I found out that
their recommendation engine was in the works. When I did find out
about their engine, my first instinct was ‚ÄúOh damn, I’ve wasted so
much time for something that will end up being useless!” [However] I decided to
finish DiggFilter and put it online regardless.

How much time would you say you’ve spent on making this service?

Approximately 200 hours, give or take a few.

We think that the service is a great one, and we hope that
Digg gives you some support and at least thanks you for your efforts.
Thank you Dmytro for taking the time to answer our questions.