Bibliometric and content analysis of the internet of things research: a social science perspective

The aim is to reveal contemporary research trends and patterns in Internet of Things (IoTs) so that social scientists who are new to the discipline may be steered towards rightful directions when examining this phenomenon.

A total of 169 IoT articles indexed in the Web of Science database were analyzed via bibliometric analysis and content analysis. The VOSViewer software was used to identify popular keywords of the IoT topics, its publication productivity, the most relevant journals, and the most prolific authors within. Content analysis was conducted manually to determine the most popular research methods used, the most frequently studied contexts, the most popular IoT application areas, the most highly examined user perspectives, and the most often employed theories.

The synthesis of both the bibliometric and content analysis results suggest the necessity of investigating the post-adoption technology usage behavior of IoT technology in developing countries, particularly in smart home. This is especially so from new landscapes using other theories or models, apart from the overwhelmed Technology Adoption Model (TAM) and its variants.

With a focus on addressing the state-of-the-art of IoT in social science, and to synthesize its future research directions systematically, this study was conducted with both bibliometric and content analysis, in order to enhance the overall analysis for higher accuracy and more reliable results.