Determining the relative importance of webpages based on social signals using the social score and the potential role of the social score in an asynchronous social search engine

Abstract

There are many ways to determine the relative importance of webpages. Specifically, a method that has proven to be very successful in practice is to value a webpage based on its position in the hyperlinked graph of the web. However, there is no generally applicable algorithm to determine the value of webpages based on an arbitrary number social signals such as likes, tweets and shares. By taking such social signals into account a more democratic method arises to determine the value of webpages. In this article we propose an algorithm named the Social Score that takes into account an arbitrary number of social signals to determine the relative importance of a webpage. Also, we present a worldwide top fifty of webpages based on the Social Score. Last, the potential role of the Social Score in an asynchronous Social Search engine is evaluated.