Citation: Khetarpaul, Sonia. "Mining location based social networks to understand the citizen’s check-in patterns." Computing 103, no. 12 (2021): 2967-2993. Published on: October 2021.
Abstract: Analyzing and understanding the movement patterns of the citizen’s with in a city, plays an important role in urban and transportation planning. Though many recent research papers focused on mining LBSN services data and performed in-depth analysis of users’ mobility patterns and their impact on their social inter-connections and friends. This paper focuses on understanding the Citizen’s movement patterns of socially interconnected users in friendship networks, by analyzing their spatial-temporal footprints/check-ins. The aim of this paper is to find the impact of structural patterns hidden in the nodes of a friendship network and external environment changes on the check-in patterns of the users. First, we classify each spatial check-in event based on its cause into either self-reinforcing behavior or social influence or external stimulus. Then we mine the collective behavior of the all the users during some special events.
