Combining Co-Citation Clustering and Text-Based Analysis to Reveal the Main Development Paths of Smart Cities

Bibliometrics is a powerful tool for analyzing knowledge domains and revealing their cognitive-epistemological structure. Different mathematical models and statistical techniques have been proposed and tested to carry out bibliometric analyses and demonstrate their effectiveness in uncovering how fields of research are intellectually structured. These include two hybrid techniques that allow clusters of related documents obtained from a co-citation analysis to be labeled using textual data. This paper reports on the findings of a bibliometric study in which these hybrid techniques are combined to: (1) build and visualize the network of publications shaping the intellectual structure of the smart city research field by considering the first two decades of literature dealing with this subject; (2) map the clusters of thematically-related publications; and (3) reveal the emerging development paths of smart cities that each thematic cluster represents and the strategic principles they embody. The five development paths which the analysis uncovers and the strategic principles each stands on are then compared by reviewing the most recent literature on smart cities. Overall, this bibliometric study offers a systematic review of the research on smart cities produced since 1992 and helps bridge the division affecting this research area, demonstrating that it is caused by the dichotomous nature of the development paths of smart cities that each thematic cluster relates to and the strategic principles they in turn support