Spatiotemporal Change-Points in Development Discourse: Insights from Social Media in Low-Resource Contexts

2026-01-10

arXiv.org

AI Summary

This study investigates the spatiotemporal evolution and critical turning points of public discourse on development issues in resource-constrained settings. Drawing on a mixed-methods analysis of geotagged social media data from Zambia spanning over two years, the research integrates topic modeling, time-series change-point detection, and qualitative coding to identify seven recurring thematic clusters. It successfully links policy events—such as the COVID-19 pandemic and a geothermal energy project—to specific discursive shifts. The work introduces the concept of “persistent discourse” to differentiate the distinct mechanisms through which short-term crises and long-term infrastructure initiatives shape public conversation. By revealing structural transformations in development discourse, this study offers theoretical and practical insights for Information and Communication Technologies for Development (ICTD) and Human-Computer Interaction (HCI), particularly regarding localized forms of civic engagement.

Technology Category

• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Topic discovery and tracking
• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Security and Privacy: Data transparency and provenance

Abstract

This study investigates the spatiotemporal evolution of development discourse in low-resource settings. Analyzing more than two years of geotagged X data from Zambia, we introduce a mixed-methods pipeline utilizing topic modeling, change-point detection, and qualitative coding to identify critical shifts in public debate. We identify seven recurring themes, including public health challenges and frustration with government policy, shaped by regional events and national interventions. Notably, we detect discourse changepoints linked to the COVID19 pandemic and a geothermal project, illustrating how online conversations mirror policy flashpoints. Our analysis distinguishes between the ephemeral nature of acute crises like COVID19 and the persistent, structural reorientations driven by long-term infrastructure projects. We conceptualize"durable discourse"as sustained narrative engagement with development issues. Contributing to HCI and ICTD, we examine technology's socioeconomic impact, providing practical implications and future work for direct local engagement.

Problem

• spatiotemporal change-points
• development discourse
• low-resource contexts
• public debate
• social media

Innovation

• change-point detection
• topic modeling
• durable discourse
• mixed-methods pipeline
• development discourse