'Will you consider legalising marijuana so that the government can regulate it, tax it, put age limits on it, and create millions of new jobs and create a billion dollar industry right here in the US'.
'Will you consider legalising marijuana so that the government can regulate it, tax it, put age limits on it, and create millions of new jobs and create a billion dollar industry right here in the US'.
Not since the terms widget, rss and web 2.0 has a term be bandied about with quite such enthusiasm as OpenSocial. In some ways this is no bad thing, enthusiasm and excitement from technologists continues to find it's way to the boardrooms.
However, where you find enthusiasm you often find confusion and inconsistency. There unquestionably a lack of understanding as to what OpenSocial actually is, what it can do for media companies today and what it could do in the future.
In part the confusion highlights Google's own shortcomings in explanation and presentation. OpenSocial is primarily a tool for developers but when one of the world's largest, most powerful and influential companies announces it's teaming up with other large high profile companies (e.g. MySpace), it will attract attention from anyone thinking about the future of media.
Different products but to labour the point see how Apple announces a product:
and compare it with the Google effort:
You can see Google haven't really attempted to explain what OpenSocial means for users. Here's my unofficial quick-fire interpretation for those more interested in AIs than APIs:
What is Open Social:
What does this mean for media companies:
Where might OpenSocial go from here:
What this means for media companies:
Summary:
I’ve started looking at what are the most engaging social networks for US users. Comscore lists 174 sites in its social networking category. I ranked the sites by two key measures of engagement:
The most engaging social networks by PVs per visitor (I cut off the list for sites with less than 100 PV/User/month: Re-ranking by visits/month (and cutting off at 4 visits per month or once a week) gives the following list:

Re-ranking by visits/month (and cutting off at 4 visits per month or once a week) gives the following list:

Several issues need to be addressed before social networks and social media portals serve their user base better. One of these issues is better understanding the different relationshis on the social graph.
Currently, everyone is a “friend”, which says nothing about our true relationship with the people we meet on-line. So we need a more fine-grained approach, to discern a true friend from a simple acquaintance. Twitter have begun to address this by allowing you distinguish between people you ‘follow’ and friends. However, one of the biggest issues yet to be tackled is social graph decay. The barrier and social implications of adding friends are lower than removing people you no longer keep-up or fall out with.
In my social network operating system of the future, trust will work a lot like PageRank (and other web ranking algorithms) do today: as a statistical analysis of a variety of factors, including some degree of explicit rating, but not depending on it.
Take the phone and email, for example. There is lots of great metadata to be collected: how often do I communicate with this person? How quickly do I respond when they contact me? How often do I initiate communication, and how quickly do they respond? How long have we been in contact? How many different modalities (phone, email, IM, other) do we use to connect? Add in: are we in the same organization? Do we work together in other ways? Do we appear in pictures together? Do I subscribe to their RSS feed?
There’s a long way to go here, but I think there are breakthroughs to be had. Obviously, the automated trust metrics will get you only so far, but it would seem that they could produce a list for manual review and management.





