Beyond Chatter: Profiling Community Discussion Networks in Urban Infrastructure Projects

The relevance of social networks in engaging communities in planning and project decision making has been established. This case study work analyzes the social and semantic networks for the Twitter accounts of four large light rail transit (LRT) projects in North America. These networks portray typical features of social networks: consistent small-world behavior, formation of stable subcommunities, and dynamic variation in topic and issues discussed with changes to the project conditions. The proposed methodology can be helpful to future projects—mainly because the cases were analyzed with an additional focus on the dynamics of social networks of participants. In early stages of the projects, these networks have a limited group of participants. As time passes and more interest is cumulated in the project, the number of nodes increases but the number of connections (between the nodes) does not increase at a similar speed. This reduces the overall density of the network and, at the same time, creates “hub” nodes. These are influential participants with an impact on the information diffusion and formation of opinions. The subcommunities that form evolve in membership, density, and topics of interest, in accordance with the project progress. Citizens migrate between subcommunities, mainly based on the central topics of discussion and, partially, the addition or migration of influential nodes. The use of the proposed methodology can be helpful to future projects because it showcases a sociosemantic approach for the analysis of stakeholders. This can help decision makers to not only understand what is on the mind of communities, but also track how such thoughts (issues) evolve over time and what the role of key players is in forming or changing the issues. A careful analysis over the project life span can help the decision makers to predict some of these trends and, accordingly, shape the project communication strategy in a more proactive fashion to meet the possible community needs. In the era of unstructured big data, this methodology can help practitioners to study the impact of decisions made or scope deviations in a project on the themes and levels of interest of local communities. Both of these two features will help to transfer public communication in construction mega-projects from a one-way outreach to a two-way interaction: try to understand/predict community issues, gather community interests and concerns, and study how community structure and views change based on the changes made to the project scope.