Ranking Parameters based on Social Network for User-generated Video Contents

Abstract

In the Web 2.0 era, people not only read web contents but upload, view, share, and evaluate all contents on the web. This leads us to introduce a new type of social network that is based on user activity and content meta-data. Moreover, we can determine the quality of related contents using this new social network. Based on this observation, we introduce a ranking algorithm for user-generated video sharing website like YouTube. We make use of pre-analysis over ranking parameters that we offer as key factors in our algorithm computation. Then, we calculate the value of contents, and orders the contents by statistical method.