A collaborative names recommendation in the Twitter environment based on location

Friendster, Facebook, Twitter and many other microblogs have been introduced since 2004. These web 2.0 applications have become a powerful tool for communication. Each social web site has millions of users whose interact with each other regardless of their location and distance. Therefore, the mechanism of recommendation system for these sites is important for users to find suitable friends. Name recommendation should be made based on the concept of homophily which stated that relationships between individuals who have in common is higher than individuals who have nothing in common. Twitter is one of the popular social web sites that were developed in 2006. Many of the Twitter users are passive users. They just follow other users but on the other side they do not have many followers. This problem arises because reciprocal relationship is not required in Twitter. To overcome this problem, a recommendation system can help users in searching friends by taking into account reciprocal relationships. The main goal of this study is to use collaborative filtering techniques to recommend names based on geographical location. User's location is taken from the user's profile by using coordinates of latitude and longitude. Celebrities profile data sets provided by the Korea Advanced Institute of Science and Technology (KAIST) are taken for testing purposes. The result of the testing indicates the potential of exploiting geographical locations in collaboratively recommending names within Twitter environment.