📚 New Book Chapter: Integrating Natural Language Processing in Human Geography

We are pleased to share a new publication co-authored by Bing Zhou, Binbin Lin, Lei Zou, Mingzheng Yang, Hao Tian, and Heng Cai, titled “Integrating Natural Language Processing in Human Geography,” published in the book GeoAI and Human Geography: The Dawn of a New Spatial Intelligence Era (Editors: Xiao Huang, Siqin Wang, John Wilson, Peter Kedron).

Human geography examines human activities and interactions with the physical world across cultural, economic, political, social, health, and transportation domains. With the rapid growth of textual big data, natural language processing (NLP) offers powerful tools for retrieving fine-grained geographic information and uncovering patterns in human perspectives, feedback, and behaviors at unprecedented scale and efficiency.

Integration of NLP in Human Geography

This chapter outlines two main ways NLP can be integrated into human geography: geoparsing from text and knowledge discovery from geographic narratives. Through two COVID-19–related case studies, the authors demonstrate the value of NLP methods:

1. Geoparsing and semantic analysis to locate vulnerable communities during strict lockdowns and identify urgent needs expressed in online help requests.

2. Sentiment analysis of social media data to explore public emotions across demographic groups, while addressing bias between social media populations and real-world demographics.

   
   

The chapter concludes by discussing the challenges and future directions for applying NLP in human geography, highlighting the promise of this interdisciplinary approach in research and practice.

Crowdsourced platform for mutual-help requests during health crises

Social media derived public sentiment on COVID-19 by gender and age groups

🔗 Read the full chapter here