A significant fraction of today's Internet traffic is associated with popular web sites such as YouTube, Netflix or Facebook. In recent years, major Internet websites have become more complex as they incorporate a larger number and more diverse types of objects (e.g. video, audio, code) along with more elaborate ways from multiple servers. These not only affect the loading time of pages but also determine the pattern of resulting traffic on the Internet. In this thesis, we characterize the complexity of major Internet websites through large-scale measurement and analysis. We identify thousands of the most popular Internet websites from multiple locations and characterize their complexities. We examine the effect of the relative popularity ranking and business type of the complexity of websites. Finally we compare and contrast our results with a similar study conducted 4 years earlier and report on the observed changes in different aspects.