An Empirical Research On Link Classification—Base On Link Motivation

With the continuous development of Webometrics and link analysis, more and more studies have confirmed that the simple counts of links between pages can not be completely reliable as a link analysis research indicators. The reason is partly because that:in a complex network environmentthere, there is a lot of worthless links. On the other hand, it is due to the existence of this variety of different motivations behind the links. Some researchers have tried to find an alternatives to link counts in link analysis, and some researchers begin to study the reasons or meanings about the web links’ creation. In theory research, the researchers have realized that some of the traditional link analysis theory does not classify the links well, and have few discussion about link motivation. Thus, the focus on link motivation and link classification is gradually becoming a new research trend.I refer to the basic theoretical models of motivation theory to examine the link motivation and link behavior. In the study, I divide links into internal links and external links. When studying external links, I separate the study of internal links accroding to the link source pages and goal pages. Using the methods of motivation theory and scenario analysis, considering the user, link pages content and scenarios, make an integrated mining on link motivation. On this basis, distinguish the links with complex motivation to build a scientific classification system of links. Then I make an empirical research on Chinese and American university website to test the link classification method and draw relevant conclusions.This study has the following innovation:(1) The traditional link analysis is mainly focus on the number of links, number of pages and other quantitative indicators to drawing some appropriate conclusions. In fact, it is built on a less strict assumptions-all links are meaningful and undifferentiated. Research result based on this assumption is actually not reliable. Among the actual condition of the network, links can be meaningless; and different links have different connotations. To really use link analysis as a research tool of webometrics, we must clarify the deeper meaning inherent in the different links. In this paper, considering the difference between the links, make link motivation as a starting point to study the differences between the links in order to improve link analysis theory.(2) On the research of links classification and link motivation, the former researchers mainly focus on external links. In this paper, I study both external links and internal links, then make classification of them. This attempt may improve the research paradigm of link motivation.(3) Early researches on link motivation keep drawing the citation analysis method until realized that the network link behavior is quite different from the behavior of the literature citation, and eventually turn to other research methods. Currently, study on link motivation is lack of a union standard. This paper emphasizes the behavioral properties of links, lists the four elements of link, learning the motivation theory, using the means of simulated scenarios, make a systematic study on link motivation.