Integrating Natural Language Processing in Human Geography

Bing Zhou, Binbin Lin, Lei Zou, Mingzheng Yang, Hao Tian, Heng Cai

Abstract: Human geography places attention on human activities and interactions with the physical world, which covers a wide range of topics such as cultural, economic, political, social, health, and transportation. The application of natural language processing (NLP) enables fine-grained information retrieval from an array of textual big data available nowadays. It offers a novel avenue to understand human perspectives, feedback, and behaviors at a larger scale and higher efficiency. This chapter illustrates how NLP can be integrated into human geography by providing two major ways of interaction: geoparsing from texts and knowledge discovery from geographic narratives. This book chapter demonstrates the use of NLP techniques in human geography through two case studies relevant to a global pandemic, COVID-19. The first one locates the vulnerable communities with geoparsing tools and identifies the urgent needs of them during strict lockdown by investigating the content of the online help requests using semantic analysis. The second case study explores the public emotions of different demographic groups by sentiment analysis and social media data and proposes solutions to alleviate the estimation bias due to the discrepancy between real-world populations and social media users. The challenges and future directions of leveraging NLP in human geography are discussed at the end of the chapter. This chapter forms an overarching understanding of the fusion of NLP and human geography and underscores promising future research and practice in this direction.

External IDs:doi:10.1007/978-3-031-87421-5_4