Abstract: Currently, there is excessively growing information
about places on Facebook, which is the largest social network but
such information is not explicitly organized and ranked. Therefore
users cannot exploit such data to recommend places conveniently and
quickly. This paper proposes a Facebook application and an Android
application that recommend places based on the number of check-ins
of those places, the distance of those places from the current location,
the number of people who like Facebook page of those places, and
the number of talking about of those places. Related Facebook data is
gathered via Facebook API requests. The experimental results of the
developed applications show that the applications can recommend
places and rank interesting places from the most to the least. We have
found that the average satisfied score of the proposed Facebook
application is 4.8 out of 5. The users’ satisfaction can increase by
adding the app features that support personalization in terms of
interests and preferences.