Towards advanced social media metrics: understanding the diversity and characteristics of Twitter interactions around science

Abstract

The increasing popularity of Twitter in both scholarly communication and public engagement with science has triggered widespread Twitter interactions around scientific information, thus giving rise to the emergence of scholarly Twitter metrics which aim to measure and characterize Twitter interactions related to scholarly objects. For the sake of more advanced scholarly Twitter metrics, the overarching aim of this PhD dissertation is to characterize diverse forms of Twitter interactions around scientific papers to understand in greater-depth the Twitter reception of scientific information and improve scholarly Twitter metrics. To this end, this dissertation starts with large-scale analyses of how many and how fast scientific papers are mentioned on Twitter in comparison with other types of social media metric data sources, to unravel the broadness and speed of Twitter presence of scientific papers. Then, focusing on scholarly tweets of scientific papers per se, this dissertation investigates the characteristics of diverse user interaction behaviors around scholarly tweets, shedding light on their potential value in developing more advanced indicators for measuring deeper levels of Twitter reception of scientific information. Finally, based on the main findings, this dissertation further discusses the possibility to approach a more fine-grained indicator system of scholarly Twitter metrics.