What Is TrustRank?

Understand how this algorithm will affect the visibility of your digital assets

TrustRank

The origins of TrustRank date back to 2004 with the publication of an academic paper titled 'Combating Web Spam with TrustRank' by Zoltan Gyongyi and Hector Garcia-Molina whilst at Stanford University.
In a nutshell TrustRank was an automated method to identify & filter authentic sites with genuine content from those that are designed to fool search engines with spam & dubious SEO methodologies.
The basics of TrustRank relies on a set of seed pages that are analysed to ensure unquestionable reliability, authority & reputation. A crawl from this seed set locates similarly reliable pages with similary positive reputation. The nearer a page sits to the seed set, the higher it's perceived TrustRank will be in theory.

In contrast to the above scenario TrustRank can also apply the same logic to spam sites & those with questionable reputation & authority. Pages that are located near to these sites & pages will attract negative TrustRank as they are 'guilty by association'.

The TrustRank network & TrustRank algorithm managed by TrustRank.org is a hybrid of the original Google TrustRank algorithm that verifies an assets reputation, authority & content alongside a myriad of additional ranking factors to ascertain it's value.
Once the algorithm is satisfied that a site surpasses a defined level of TrustRank, a relevant, similarly authorative asset is linked with it. The purpose of this match-making exercise is to ensure that every link is ethical & legitimately present to enhance value & benefit to the end user. Of course from a commercial prospective the purpose of TrustRank is multilayered.

Primarily commercial entites strive to ensure that existing & potential clients extract optimum value from their digital content & this is only truly achievable via an organised link methdology programme such as TrustRank networking.
The benefits to the organisation continue in the shape of enhanced reputation, increased organic traffic & visibility. Google's origins were based on rewarding providers of informative, unique, legitimate & critically, relevant content. PageRank, Panda, Penguin etc were each implemented over the years with the primary aim of enforcing the company's ethos; punishing & rewarding providers based on how well (or otherwise) they aligned their content to Google's end goals.

The 2019 version of TrustRank is not so far removed from the initial framework set out within the Stanford paper however the web has of course changed beyond recognition over the past 17 years as has optimisation & Google's penalization methods. The TrustRank network & associated algorithm is however 100% committed to the initial aims of Google's founders Larry Page & Sergey Brin who identified the need to separate quality from spam. Similar to Search Engine Optimization (SEO), TrustRank is a contrived methodology however this should never be misunderstood or attract any negative connotations as by default every webmaster, organisation & content provider has a duty to regulate & manage their asset's associations & collaborations. The biggest problem for the aforementioned is their general inability to technically apply such management. Amateur attempts will almost uncertainly end with ineffective links & at worst penalization which is precisely why professional SEO or computer science intervention is such a critical success factor to optimisation.

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