Predictors of users' willingness to personalize web search

Personalized Web search offers a promising solution to the task of user-tailored information-seeking; however, one of the reasons why it is not widely adopted by users is due to privacy concerns. Over the past few years social networking services (SNS) have re-shaped the traditional paradigm of information-seeking. People now tend to simultaneously make use of both Web search engines and social networking services when faced with an information need. In this paper, using data gathered in a user survey, we present an analysis of the correlation between the users' willingness to personalize Web search and their social network usage patterns. The participants' responses to the survey questions enabled us to use a regression model for identifying the relationship between SNS variables and willingness to personalize Web search. We also performed a follow-up user survey for use in a support vector machine (SVM) based prediction framework. The prediction results lead to the observation that SNS features such as a user's demographic factors (such as age, gender, location), a user's presence or absence on Twitter and Google+, amount of activity on Twitter and Google+ along with the user's tendency to ask questions on social networks are significant predictors in characterising users who would be willing to opt for personalized Web search results.