Social Intelligence Mining: Transforming Land Management with Data and Deep Learning - Mohammad Reza Yeganegi; Hossein Hassani; Nadejda Komendantova (Land, 2025)
The integration of social intelligence mining with Large Language Models (LLMs) and unstructured social data can enhance land management by incorporating human behavior, social trends, and collective decision-making. This study investigates the role of social intelligence—derived from social media—in enhancing land use, urban planning, and environmental policy crafting. To map the structure of public concerns, a new algorithm is proposed based on contextual analysis and LLMs. The proposed method, along with public discussion analysis, is applied to posts on the X-platform (formerly Twitter) to extract public perception on issues related to land use, urban planning, and environmental policies. Results show that the proposed method can effectively extract public concerns and different perspectives of public discussion. This case study illustrates how social intelligence mining can be employed to support policymakers when used with caution. The cautionary conditions in the use of these methods are discussed in more detail.