征文启事 | TUS专刊《社会感知驱动的时空数据挖掘：方法与应用》等你来

The proliferation of mobile devices and location-based platforms has established social sensing as a primary paradigm for capturing human activity and environmental dynamics at scale. This ubiquitous sensing layer generates massive volumes of user-generated content characterized by heterogeneous formats and distinct spatio-temporal signatures. These complex data streams present significant computational challenges to traditional analytical frameworks due to their high noise levels, semantic ambiguity, and non-linear dynamic correlations. Spatio-temporal data mining consequently serves as the essential methodological infrastructure for transforming these raw sensory inputs into actionable structural knowledge. Advanced mining algorithms function to extract latent patterns from crowd behaviors and reveal the underlying physical and social mechanisms of urban evolution. Computational frameworks utilize these historical spatio-temporal dependencies to model system dynamics and forecast future trends in human mobility and collective events. The integration of these mined insights further supports critical decision-making processes across urban planning, emergency response, and public health management. This special issue aims to consolidate contributions that advance the theoretical foundations and practical utility of mining social sensing data.

移动设备和位置服务平台的普及使社会感知成为大规模捕获人类活动和环境动态的主要范式。这一泛在感知层产生了海量用户生成内容，具有异构格式和独特的时空特征。这些复杂数据流因其高噪声水平、语义模糊性和非线性动态关联，对传统分析框架提出了重大计算挑战。时空数据挖掘因此成为将原始感知输入转化为可操作结构化知识的核心方法基础设施。先进的挖掘算法从群体行为中提取潜在模式，揭示城市演化的内在物理和社会机制。计算框架利用历史时空依赖关系建模系统动态并预测人类出行和集体事件的未来趋势。这些挖掘洞察的整合进一步支撑了城市规划、应急响应和公共卫生管理等关键决策过程。本专刊旨在汇集推进社会感知数据挖掘理论基础和实践应用的研究成果。

This publication invites original research concerning the complete pipeline of spatio-temporal data mining within the specific context of social sensing. We invite submissions across a broad spectrum of scholarly formats, ranging from theoretical frameworks and methodological innovations to empirical case studies and systematic reviews.

本刊征集涉及社会感知背景下时空数据挖掘完整流程的原创研究。欢迎提交从理论框架、方法创新到实证案例研究和系统性综述等多种形式的稿件。感兴趣的主题包括但不限于：

Submissions should be prepared according to the “Submission Guidelines” available on the journal homepage https://us.sagepub.com/en-us/nam/transactions-in-urban-data-science-and-technology/journal203731#submission-guidelines. Please visit the Journal’s submission site https://mc.manuscriptcentral.com/tus to upload your manuscript. Submitted papers should not have been previously published nor been currently under consideration for publication elsewhere.