A Review on Recommendations and Overlapping Communities for Location Based Social Networks

Abstract — Today, a location based social networks is a drastically growing area which attracts users attention towards itself. Location based social networks(LBSN) assist between real world and online social networks by allowing users to check-in at a physical place and share the locations/location related contents with their friends. This Location sharing can be through GPS, mobile email or text. Location related contents can be geo-tagged photos and notes. LBSN sites includes foursquare, brightkite, GyPSii, Citysense etc. Many other online social networks provides activities ( such as following, grouping, voting, tagging, etc.) that helps to interact with the virtual world but, “check-in ” reflects a user’s geographical action in the real world, residing where the online world and real world intersect. Location data helps to understand the users preferences and behaviour. People in the social structure naturally forms a community among themselves. For example, a person usually belongs to several social groups such as family, friends, and colleges. Usually, these communities in a social network can overlap each other. Detecting overlapping communities is very important to understand and analyze the structure of social network. Recommendations help to suggest the opinions to the friends and family members. Friends have a good relationship among themselves. Hence, they try to recommend the things that can be useful to the persons closest or nearer to them. This paper reviews the overlapping communities structure, algorithms for overlapping community detection and recommendation based on location and friend