Development and evaluation of a facebook-based product advisor for online dating sites
Social networks play an important role in Web 2.0. For many users establishing contacts and staying in touch in the virtual world is more than just a spare time filler. In social networks like Facebook they provide much information about themselves in user profiles. Also for online dating the focus is on establishing new contacts. In general, three types of dating sites can be distinguished: more serious dating agencies, less focused singles' platforms, and casual dating sites. In the proposed paper we develop a product advisor that uses the Facebook profile information provided by a user to classify her or him to one of the three dating site categories which is most suitable for the user's purpose. For classification we use Naive Bayes. To train the classifier we investigate the correlation between profile information and choice of dating sites. We also evaluate this correlation on collected data of representative German dating sites. Although a sharp distinction is hard to find, tendencies and enlightening insights are revealed by the collected data.
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