Characterizing user behaviors in location-based find-and-flirt services: Anonymity and demographics: A WeChat Case Study

WeChat, both a location-based social network (LBSN) and an online social network (OSN), is an immensely popular application in China. In this paper we specifically focus on a popular WeChat sub-service, namely, the People Nearby service, which is exemplary of a find-and-flirt service, similar to those on Momo and Tinder. Specifically, the People Nearby service reads in the current geographic location of the device to locate a list of other people using WeChat who are in the same vicinity. The user can then request to establish a WeChat friendship relation with any of the users on the list. In this paper, we explore: (i) if one gender tends to use the People Nearby service more than another; (ii) if users of People Nearby are more anonymous than ordinary WeChat users; (iii) if ordinary WeChat users are more anonymous than Twitter users. We also take an in-depth examination of the user anonymity and demographics in a combined fashion and examine: (iv) if ordinary WeChat females are more anonymous than ordinary males; (v) if People Nearby females are more anonymous than People Nearby males. By answering these questions, we will gain significant insights into modern online dating and friendship creation, insights that should be able to inform sociologists as well as designers of future find-and-flirt services.