A spatial-temporal public opinion analysis of IP location disclosure on Chinese social media platforms using Weibo data

Keywords: IP location, public opinion, Weibo, location privacy, spatial-temporal analysis, topic model
Abstract Type: Paper Abstract

Abstract

On April 28, 2022, the Chinese social media platform, Weibo implemented a new feature that automatically adds a user's location (determined by IP addresses) to all posts and comments. In this work, we analyze users' reactions to this implementation. Exploratory spatial-temporal analysis was conducted on a wide range of content with the goal of understanding the general trends and major themes of the discussion. A Latent Dirichlet Allocation (LDA) topic model was used to extract implicit topics from the discourse. Results indicate that both supporters and opponents of the mandatory location disclosure participated in the discussion, with females more involved than males. Location privacy concerns were also interpreted through hashtags and LDA-derived topics, and the variation between local and overseas Chinese opinions was compared. The findings of this study will aid policymakers in understanding public concerns about mandatory location disclosure and help developers implement privacy-aware designs in the context of contemporary China.