Using Location-Based Social Media Data to Observe Check-In Behavior and Gender Difference: Bringing Weibo Data into Play

Muhammad Rizwan , Wanggen Wan (1) , Ofelia Cervantes (2) , Luc Gwiazdzinski (3)

1 Shanghai University
2 University of the Americas (Universidad de las Américas Puebla, UDLAP), Puebla 72810, Mexico
3 PACTE - Pacte, Laboratoire de sciences sociales

Population density and distribution of services represents the growth and demographic shift of the cities. For urban planners, population density and check-in behavior in space and time are vital factors for planning and development of sustainable cities. Location-based social network (LBSN) data seems to be a complement to many traditional methods (i.e., survey, census) and is used to study check-in behavior, human mobility, activity analysis, and social issues within a city. This check-in phenomenon of sharing location, activities, and time by users has encouraged this research on gender difference and frequency of using LBSN. Therefore, in this study, we investigate the check-in behavior of Chinese microblog Sina Weibo (referred as " Weibo ") in 10 districts of Shanghai, China, for which we observe the gender difference and their frequency of use over a period. The mentioned districts were spatially analyzed for check-in spots by kernel density estimation (KDE) using ArcGIS. Furthermore, our results reveal that female users have a high rate of social media use, and significant difference is observed in check-in behavior during weekdays and weekends in the studied districts of Shanghai. Increase in check-ins is observed during the night as compared to the morning. From the results, it can be assumed that LBSN data can be helpful to observe gender difference.

Mots clés: big data; social network; lbsn; check-in; gender difference

Domaines: Sociologie; Science politique; Architecture, aménagement de l'espace; Géographie

Muhammad Rizwan, Wanggen Wan, Ofelia Cervantes, Luc Gwiazdzinski. Using Location-Based Social Media Data to Observe Check-In Behavior and Gender Difference: Bringing Weibo Data into Play. ISPRS International Journal of Geo-Information, 2018, 7 (5), pp.1-17. ⟨10.3390/ijgi7050196⟩. ⟨halshs-01811236⟩