Ever since it first started ranking pages Google has been in the influence business – the influence of content.
Gaining content influence has been the role of SEO but, regardless of how often Google re-writes the rules and modifies the algorithms, this can be gamed.
A new way is needed.
For a while now, I have been saying that data hosts such as Google, Facebook and Twitter are better placed to gauge influence due to having full access to data within their own environment.
Is Google putting together the building blocks of an internal influence measurement system? By combining data compiled from different sources Google can paint an accurate picture of who we are, what we like and what we do within its ecosystem.
Consider these elements and how they all help Google paint a picture:
- Page Rank
- Author Rank
- Analytics, and now
As Bill Slawski advises, a patent granted to Google in December last year details how Google could use the “content propagation likelihood” – or, how well things spread – of items (here called entities) you share, endorse, comment on etc. to determine what content could be placed before a user. According to the abstract:
A user’s content propagation likelihood is computed using weighted measures of various ways in which an entity can spread through a social network. A user’s content propagation likelihood may also be set for a given vertical (e.g., music, sports, etc.) and/or a given media type (e.g., images, videos, etc.) that pertains to the particular user.
I have said elsewhere that “virality is an extension of influence” and, considering the possible extension to topic and media type, fits with the relevance criteria I outlined in The 3 R’s of Influence.
Of course, unlike influence measurement systems such as Klout and Kred, Google will not be labelling us with a score (at least not one that’s publicly visible) – instead, our “rating” will be seen in SERPs, in suggested user lists and even for alternative content views on Plus should Google ever wish to explore this avenue.
As I wrote in ‘Influence redefined‘:
We cannot rely on a single system to calculate influence for all and we also cannot rely on a single score to reflect our own influence and reputation across the whole social web; moving to service specific grading may be a viable alternative.
Google will employ any internal influence measuring system as a means to ensure that users, and their connections, continue to see the most relevant information based on all the data available across its product base.
Is Google building it’s own influence engine? Based on all the existing and potential elements that could be brought to bear, absolutely! What is certain, however, is that it will be unrecognisable from any existing influence measurement system if it is even visible to the end user at all.
Image by John Harwood