Shadows and Light: Unveiling Multifaceted Polarization in Social Media Discourse on Human Trafficking
2025-07-29
Human trafficking, a grave human rights violation with far-reaching global consequences, serves as a compelling case study for analyzing multifaceted polarization dynamics in online discourse and the influence of social media on public perceptions and responses. Drawing on social identity theory and self-categorization theory, this article aims to elucidate both group polarization and opinion polarization surrounding human trafficking on social media. Through an integrated approach that combines clustering, social network analysis, text mining, and topic modeling, this study provides a comprehensive examination of community formation, influential actor identification, topic classification, and semantic analysis. The similarity between user-generated content from clustered groups and the topics identified is calculated to quantify the degree of multifaceted polarization. The findings reveal a robust community structure within the network and uncover divisions and structural characteristics across each subgroup. Utilizing the BERTopic model, thematic clusters such as vulnerable groups, persecution experiences, incident areas, law and politics, public awareness, contraband, and case events are identified, reflecting the primary public concerns regarding human trafficking. This research enhances our understanding of multifaceted polarization shaped by social identity in digital conversations about critical social issues and holds significant implications for policymakers, advocacy groups, and practitioners navigating public opinion regarding human trafficking in the digital realm.