Author: Khansa Kiasatina

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Gaming the PageRank System

Having your website ranked high on search engines is a huge advantage to anyone. You or your company’s name would become more well-known, more traffic would be driven to your website, and then ultimately, you would benefit through increased sales or positive exposure.

These are a few of the many reasons why someone would want to increase the PageRank for their website, which is a concept we have discussed intensively in class. One strategy to artificially inflate PageRank is to participate in a Spam Farm, which is also what we’ve seen in one of our assignments. As it turns out, Google disallows this setup—called a “link scheme”—in a document of theirs called “Webmaster Guidelines”.

“Webmasters who spend their energies upholding the spirit of the basic principles will provide a much better user experience and subsequently enjoy better ranking than those who spend their time looking for loopholes they can exploit.”

– Google’s Webmaster Guidelines

It obviously makes sense to disallow link schemes—otherwise, the Internet would be full of pages of websites that links to many other websites, which is clearly not helpful as an end-user who wants to search for actual content. Google makes sure that this doesn’t happen by detecting websites that participate in these link schemes and consequently removing them from search engines, effectively discouraging others in following suit.

However, it is still possible to be given penalties and be removed from search engines even if you follow all the rules in their “Webmaster Guidelines”.

Despite not having built a single link in years, Dan Petrovic still received a warning from Google about “buying links that pass PageRank or participating in link schemes” and had his website removed from search engines for unclear reasons. On a separate but related note, John Mueller from Google even says that you are responsible for the content on your own website, even if it has been hacked or changed, illegally or without your knowledge.

Though this doesn’t happen too often, having your pages removed from search engines can be incredibly frustrating for website owners—to the point that instead of gaming the system to increase your PageRank, you might instead try to be careful with the content and links on your website so as to not incur Google’s wrath.

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The Majority Illusion

Here are two questions to ask yourself:

  1. How is it possible that something seemingly unpopular blows up all of a sudden and becomes a trend overnight?
  2. What if it actually hasn’t become a trend, and you’re the only one who perceived it to be that way?

This phenomenon is known as the “majority illusion”—a paradox where you conceive a certain attribute as being popular just because most of the people around you have adopted it when, globally, that certain attribute is actually uncommon.

As an example, we have the figure below.

The graphs (a) and (b) form the same small world network, as discussed in class, of 14 nodes and 3 coloured ones, with the only difference between them being which nodes are coloured. In graph (a), the uncoloured nodes see that at least half of their neighbours are coloured. This, however, is not true for any of the nodes in graph (b). If we now define nodes as individuals and a coloured node as a person with a shared attribute, we can see that the “majority illusion” would only apply to the uncoloured nodes on graph (a) and not graph (b).

What makes the “majority illusion” fascinating is that only 20% of the individuals in graph (a) have a shared attribute, yet the remaining 80% would still believe the attribute is popular just because at least half of those who they are connected with have it.

The “majority illusion” does not occur in just any regular social network though. The most important aspect, as Lerman’s article states, is that the network is disassortative. In other words, the “majority illusion” is stronger in graphs where nodes of low degree are more likely to connect with nodes of high degree, and these nodes with high degree have a shared attribute, as observed in graph (a).

Perhaps it is obvious that individuals who have high degrees of edges are more influential, or that those who have low degrees of edges are more easily influenced since their circle is smaller. This, however, can be difficult to realise when you yourself are part of the network. Just like the decentralized search seen in class, we only know of the individuals adjacent to us, and do not have complete knowledge of the network.

Something we can learn from the “majority illusion” paradox is that the next time we see something becoming popular, maybe we should take a step back to check if that really is the case before we get influenced or begin to accept it as the norm. It might even be to all of our benefit to connect with more people in order to gain a wider perspective of our world—which, in fact, even supports Lerman’s article in that the “majority illusion” is weaker in graphs that are assortative.

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