Today’s web is a place where people spend considerable amount of time. Subsequently, they reveal a lot of their personal details and insights of their lives. We are beginning to understand how some of this interaction data can help us to improve user experience on web and in a way to achieve that user’s personality determination is the key aspect of making a behavior model out of it.
Personality has been shown to be relevant to many types of interactions; it has been shown to be useful in predicting job satisfaction, professional and romantic relationship success, and even preference or different interfaces. Until now, to accurately gauze users’ personalities, they were required to take a personality test. This made it impractical to use personality analysis in many web-oriented service domains.
In this Project we have developed a completely new methodology using Machine Learning to mine interaction data to determine the personality of a user.
I have the draft copy of the thesis. Click here to read it.