Identification and modelling of human behavior is always an interesting and important study since long time. Astrologers, palmists make their try to predict how an individual will behave and what move a person will take in future. Human physical aspects also considered important about the prediction of expected actions of individuals. These Bio-metric attributes consider shape of ears, forehead structures, walking style, gaze style and of course hand writing patterns also been studied a lot.
With the rapid growth of internet users till Dec 2009 ,1,802,330,457 people are using WWW i.e. 26% of the world population. The 53.5% of european uses internet and the growth rate of internet users is 305.1% in 2000-2001. However, in Asia People using WWW pages and leaving trajectories. The web pages on WWW forum provide back links and forward links to move on. Through these links a user move on and back in pursuit of his
'interest'. Once a surfer found his/her interested content, image, video or discussion on a page he get stick with it.
Clicking on back/forward links depends upon certain liking and disliking of individuals. Therefore an individual made 'clicks' and out reach his desire material.
A visualization of the network structure of the Internet by Hal Burch and Bill Cheswick, courtesy of Lumeta Corporation
An individual living in Manchester City is a fan of Manchester United, therefore, its quite simple to comprehend that why he visits so many times to view Facebook page of Manchester United. Secondly, he is expected to purchase tee shirts, shoes or other MU logo based sports wear. Moreover, not only that particular individual like MU he will also influence his (social networking Facebook, Twitter) friends. It also depends upon his own position in his social context i.e. lets consider following is the friends network over twitter (who follow whom, here we have few nodes followed by a great number of followers. So if that MU fan is one of the most centric persons over twitter or face book, then its highly predictable that he is expected to influence others about his own favorite club.
Therefore, people having similar interests are found to click similar kinds of web sites, secondly, patterns could be found from browsing history of people having common interests.
On click and browsing patterns helps us to understand common behavior of individuals having common interests. Social network analysis plays significant role in identifying communities, important individuals and cliques which reflect common attitude and behavior. This outcome can be used to develop marketing strategies and the development of computational advertisement basis.
