Web-Centric Human Mobility Analytics

Introduction

Human mobility analytics has become increasingly important in various domains including urban planning, transportation, public health, and social science. With the rapid development of web technologies and the emergence of large language models (LLMs), web-centric approaches to human mobility analytics have gained significant attention. This tutorial provides a comprehensive overview of web-centric human mobility analytics, covering methods, applications, and future directions in the LLM era. We discuss how web data sources, web-based analytical techniques, and web platforms can be leveraged to understand, model, and predict human mobility patterns. Furthermore, we explore how LLMs are transforming this field by enabling more sophisticated natural language understanding and generation capabilities for mobility data analysis.

Intended Audience

This tutorial is designed for professionals, researchers, and practitioners interested in human mobility analytics, assuming basic knowledge of AI and data analysis.

Attendees will gain understanding of mobility analytics methodologies across location, individual, and macro levels, plus advanced frameworks like federated learning and causal inference for real-world applications.