Quality models for venue recommendation in location-based social network

2014 ◽  
Vol 75 (20) ◽  
pp. 12521-12534 ◽  
Author(s):  
Weizhi Nie ◽  
Anan Liu ◽  
Xiaorong Zhu ◽  
Yuting Su
Keyword(s):  
Social Network ◽  
Quality Models ◽  
Location Based Social Network

scholarly journals A partial knowledge of friends of friends speeds social search

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255982
Author(s):  
Amr Elsisy ◽  
Boleslaw K. Szymanski ◽  
Jasmine A. Plum ◽  
Miao Qi ◽  
Alex Pentland
Keyword(s):  
Social Network ◽  
Human Mobility ◽  
Sufficient Conditions ◽  
Partial Knowledge ◽  
Social Search ◽  
Strongly Nonlinear ◽  
Original Distribution ◽  
Personal Connections ◽  
Location Based Social Network ◽  
Necessary And Sufficient

Milgram empirically showed that people knowing only connections to their friends could locate any person in the U.S. in a few steps. Later research showed that social network topology enables a node aware of its full routing to find an arbitrary target in even fewer steps. Yet, the success of people in forwarding efficiently knowing only personal connections is still not fully explained. To study this problem, we emulate it on a real location-based social network, Gowalla. It provides explicit information about friends and temporal locations of each user useful for studies of human mobility. Here, we use it to conduct a massive computational experiment to establish new necessary and sufficient conditions for achieving social search efficiency. The results demonstrate that only the distribution of friendship edges and the partial knowledge of friends of friends are essential and sufficient for the efficiency of social search. Surprisingly, the efficiency of the search using the original distribution of friendship edges is not dependent on how the nodes are distributed into space. Moreover, the effect of using a limited knowledge that each node possesses about friends of its friends is strongly nonlinear. We show that gains of such use grow statistically significantly only when this knowledge is limited to a small fraction of friends of friends.

Objectives and State-of-the-Art of Location-Based Social Network Recommender Systems

2018 ◽  
Vol 51 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Zhijun Ding ◽  
Xiaolun Li ◽  
Changjun Jiang ◽  
Mengchu Zhou
Keyword(s):  
Social Network ◽  
Recommender Systems ◽  
State Of The Art ◽  
Location Based Social Network

Towards understanding the gamification upon users’ scores in a location-based social network

2014 ◽  
Vol 75 (15) ◽  
pp. 8895-8919 ◽  
Author(s):  
Lei Jin ◽  
Ke Zhang ◽  
Jianfeng Lu ◽  
Yu-Ru Lin
Keyword(s):  
Social Network ◽  
Location Based Social Network
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