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PageRank and Human Memory

In a paper by Thomas Griffiths, Mark Steyvers, and Alana Firl (2007), the authors propose that computers and the human mind face a similar task when required to retrieve stored information in response to a query. The researchers determined that performance on a fluency task could be predicted using a concept we have covered in class: PageRank.

PageRank is a method of sorting responses to a query based on importance determined by link structure. According to the authors, many psychological theories propose a similar mechanism by which human memory operates. The targets of memory retrieval are more abstract, comprised of concepts and ideas instead of websites, but nonetheless the process is demonstrably similar. This similarity is depicted by the authors in the figure below.

Given the parallels between search queries on the internet and associations in a semantic network, it makes sense that a human memory task that closely resembles an Internet search would be well-predicted by PageRank. In the task, the researchers showed participants a letter of the alphabet, constituting a query. Participants were then asked to say the first word beginning with that letter that came to mind. This task was performed to determine the prominence of different words in the human memory. PageRank was calculated by constructing a directed graph. Each word was a node, linked to individuals who thought of that word. The researchers determined that PageRank computed from a semantic network was a good predictor of responses in the task and outperformed other common measures of how prominent words are in human memory.

This is the application of a topic we have covered in class – the PageRank algorithm – to a unexpected psychological result. In class, we learned about the efficacy of PageRank in determining the importance of results to a query, and we came to understand how PageRank dramatically shapes our experience online. However, it seems as if PageRank extends beyond the internet. Indeed, perhaps PageRank is such an elegant solution partially because it intuitively mimics our own thought processes. It is interesting to consider how psychological processes might actually shape the development of such algorithms.

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