Posts Tagged ‘connection’

content authoring + silo data still holding sway

January 12, 2011

2011 and seems to be next site to seep into the main stream of early adopters online. I describe these sort of sites as prompted content authoring.  What is unprompted content authoring?  That would be publishing a blog post.  A twitter update is also authoring (note those with a monopoly -ish athoring platform then have an exclusive over doing stuff with that data or via an API allow others to help them do so).  Authoring seems pretty straight forward to describe but prompted/unprompted seems harder to pin down as every bit of information is authored in a conversation? Right?

I want to put forward an observation to explain unprompted content authoring v prompted. Unprompted content is content authored based on an individuals free will, maybe in response to a conversation, an idea, to take issue with another post. The point is they are free to author anyway they like and additionally they are free to host and publish the content where they please.  The down side is that content will be dis- intermediated from all the other content in the information universe.  Okay, comment, track backs aid connection but are reliant on direct linking from those who know the content has been published. But who knows everything?  Prompted content authoring is constraining the context and gathers demand around that context to increase the probability of answers and of course answer are just more prompted content authoring.  For me the prompted – unprompted divide is based not on the act of authoring content per say but in setting the community environment so that more content is authored in context around aggregate demand.  The quoras are bringing efficiency to this by centralising the demand, much as Groupon does for individuals to aggregate demand for local suppliers.  I think time will show this need to centralise will be a transient period in the evolution of the web as all the ‘answers’ will be authored and all individuals will be connect in context regardless of where they author there content online (ie no one website setup for each purpose).  This decentralized demand authoring is better described in this unprompted post by EmergentbyDesign blog.


filtering social news

April 23, 2010

What are the magic ingredients that brings the best information to us in a social context?  A couple of months ago I presented the whole story on the logic going on behind  This week the development team over at facebook partially presented their model.  The techcrunch blog has a great summary.

EdgeRank is the core metric formed and a news feed is a series of Objects prioritied by edgescore.  This can be summarised in the following equation:

The Sum of all Edges = Ue * We * De

where U is the affinity score between the user and Edge creator, W weight for each edge type, D time discount.

U – is real interesting as it is trying to decide how close you, the reader of the news stream is to author of the object.  Now, FB has a great starting point, they know there is a social connection between you and the author as only friend connections are brought back into a new feeds (OK, slightly more complicated as fan pages etc or app. data may feedback object not authored by a friends ie. like a RT of a non follower on Twitter).   By contrast mepath is given no starting relationship connection, it has to decide that itself and does so based on the lifestyle context of an individual over time.

W – applies a weight based on the type of edge e.g. comment, video post etc.  In effect saying the type of media authored can be biased up or down.  That is real interesting but how these weighting are decided is of even more interest?

D – time discounting.  Real time to later time.  Everyone one wants the latest but just in case we are not logged in 24/7 then we can review top news that ‘holds’ on to some friends post for longer, minimizing the chance you missed important news.  From my thinking on time filtering data, it is a deep and complex science all on its own.  The most important information an individual wants may well have happened in the past and well into the past.

While we can segment and split all we like, the simple objective remains, bring back the best information that is possible to have for the individual.  And increasing the will found and be achieved by understanding both the context it is initiated and understanding the context in which is was authored.