Agent-based decision support for social media influence in urban planning

Abstract

A variety of social media platforms have been recently used for citizen engagement in urban planning. However, social media generate large datasets and complex relations, making it difficult for planners and policymakers to understand the influential factors on the interactions and actions of various actors. Agent-based modelling (ABM) makes it possible to capture the complex interactions between actors. However, it does not come with a mature methodology to capture and measure social media influence. Besides, most of the existing studies are from the discipline of computer science and lack approaches to make it useful for participatory planning. Therefore, this research explores an agent-based approach for measuring and simulating social networking influence in urban planning to support informed decision making. It contributes to bridging the gaps between ABM research, social media studies, and planning literature.