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Is there a googlearchy?

Do search engines help the rich (in terms of popularity) get richer (in terms …

The Proceedings of the National Academies of Science isn't the place you'd typically go for a discussion of PageRanks and surfing behavior. But the emergent complexity of the web provides the raw material for studies ranging from network dynamics to social psychology. A study released online in advance of publication looks into how the influence of search engines is affecting the accessibility of online information. The authors are examining fears that search engines will create a situation where a self-reinforcing cycle of popularity will create an Internet in which a limited number of information sources predominate: "[S]earch engines bias the traffic of users according to their page ranking strategies, and it has been argued that they create a vicious cycle that amplifies the dominance of established and already popular sites. This bias could lead to a dangerous monopoly of information."

This cycle has picked up the name "googlearchy", and the logic behind it is as follows: articles and discussions on popular site will, by default, attract the most inbound links, and appear first in search results accordingly. As such, they are more likely to attract attention that, in turn, results in further links, reinforcing their high rankings. Taken to an extreme, the authors suggest that this process has the potential to change the entire topology of the Internet into a star-shaped network dominated by a limited number of sites.

Using data regarding page rankings from Yahoo and traffic figures from Alexa, the authors tested whether this expectation held up against real-world data. They plotted the traffic vs. inbound links in such a way that the slope of the line should reveal whether page rankings increased traffic. For sites that received anywhere from about 100 to 1,000,000 inbound links, traffic and links retained a linear relationship, but the slope was nothing like predictions. Traffic increased far less than would be expected if search engines were enhancing popularity. It actually increased less than would be predicted if traffic were directly proportional to inbound links. In the end, it appears that each inbound link only increases traffic by a factor of 0.8. The results suggest that the reliance of web users on search engines is actually suppressing the impact of popularity.

This becomes even more clear when the data outside this range is examined: both at the high and low end, the curves go flat. At the low end, this suggests that low-popularity sites are retaining traffic at a rate disproportionate to the number of places that link to them. Meanwhile, at the high end, sites seem to reach saturation; regardless of their inbound links and page ranks, they cannot expand their (already considerable) audience.

The paper proposes a factor that can help explain these results: user interest. A user interested in a topic will probably have already visited the popular sites the cover that topic. Search engines allow them to identify the less-popular sites that cover areas that specifically interest them. Incorporating that factor into a mathematical model allowed them to match the curve of the page rank vs. traffic data over a broader range of popularity, and accurately predicted the saturation apparent at the high end. Their conclusions?


In other words, if you have something to say that the web-surfing community is interested in, they can still find you despite the high traffic achieved by popular sites.

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