Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach

Highlights：

• We present a novel approach for identifying clusters in a set of citation-based networks to map out interdisciplinary specialty structures.

• An ensemble of null network models was adopted to test the (inter)disciplinary composition of bibliometric clusters.

• By exploiting an original dataset, we illustrate our approach through the case of an important knowledge domain — social media data-based research.

• We add to the literature on the domain of social media data-based research by detecting an increasingly interdisciplinary trend.