Google+ Needs Algorithmic Filtering

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Google needs to install some serious filtering tools on its Google+ platform, to help users cut through the noise, says Clint Boulton

I’ve waited a week to write this post because there has been a lot of newsy stuff going on. Google+ has been newsy and topical since 28 June, but it’s also growing increasingly noisy, with what comScore claims are 20 million people using the service.

That makes for one hell of a noisebox to filter. And filtering is one area Google+ is lacking. What? Did you think I was going to write about Google+ name and blame game issues? Jay Freeman covers those well in this + post. Bores me to tears.

What I want to talk about are the collaborative filtering technologies Google needs to add to +. We’re going to need buffers and need them fast.

Algorithmic filtering

I plussed about 300 people and 1,100 people have plussed me – more than on Twitter or Facebook combined. Admittedly, I just haven’t been my own best social media shepherd or gardener, but the noise in my feed is loud.

Louis Gray, provided a great answer to the Tom Anderson post I blogged about last week. The MySpace founder fretted that Google would send its algorithms swarming all over Google+ to manage the signal-to-noise ratio, thereby taking the human element out of the collaborative filtering equation.

But Gray, who as a vice president at personalised news and social stream provider my6sense, argues that algorithmic filtering is exactly what is needed for+:

“An algorithm that surfaces personalized content that does not take into account the many multiple factors that indicate interest, from the person sharing the content, to the content source, keywords, headline, author, time of day, time since publishing, the individual(s) commenting on that message, the keywords in the headline in combination with the author and/or the source, etc. simply isn’t enough. The truth is that each of us does this automatically, and what the world needs is social networking that thinks like we do.

“For example, if you like financial news from the Wall Street Journal more than you like it from GigaOM, then similar stories from both should be weighted this way. But if you prefer articles on stock from Om Malik more than you do from Mathew Ingram, that too should be determined. The human brain is a very complex object indeed, but just because something is hard doesn’t make it something you don’t want to try.”

Or, as I noted earlier, we need serious semantic sentiment analysis tools on Google+ that manage all of the signals Gray mentioned above.

We need this because when the mainstream public is invited in, the social network will be swarmed and we will be overwhelmed. We will be forced to stop and consider who we follow and who we want to follow.

There are people on here with big brands and tens of thousands of followers, but even people who have a relatively modest 1,000-plus users following them will be assaulted by tons of notifications.

Case in point: ReadWriteWeb founder Richard MacManus just graciously opted to follow me after I followed him a while ago.

But there are 15 other notifications of new followers, spanning 30-something people whom I don’t know at all. That takes time to sort through to see if I want to follow them and it…. goes… on… all…. day… long. Signal-to-noise ratio indeed!

Contextual filtering

Gray in his post also suggested Google find a way to leverage its trove of user data for behavioural targeting to augment the Google+ filtering experience. I’ll call this contextual filtering. Capital idea, so long as people are advised their web history is being leveraged for contextual filtering. Gray wrote:

“With Google+, on both mobile and desktop, they have a new opportunity to do this correctly, continually learning more about your interests and activity to serve you the most relevant updates while avoiding much of the cruft that has plagued other networks, specifically Facebook.

“Having worked closely with my6sense for the better part of two years, I’ve seen directly how smart algorithms based on implicit feedback can make useful high quality streams out of what would more commonly be considered noise – and I’ve seen many people on Google+ and Twitter call for the same such filtering engine to be applied.”

Yes, indeed. Again, as Google+ opens to more users, the noise will be insane, with millions of people shouting in tongues. We need filtering in place. I agree with Anderson and Gray, but I think we need both Google’s help and we need to be flexible to let Google use our interest-based information as guidance. We might even fill out a check list to provide the search engine more info to target our tastes.

Something like: turn off all posts where certain topics, such as info about Google+ on Google+ (I know I, Anderson and Gray love it, but it’s too self-reflexive and Inside Baseball for some folks), or software patent in-fighting is the topic.

We should have the ability to list filter preferences and let Google do the work for us.

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