Collaboration Size and Citation Impact in Big Data Research

With rapid and widespread application, Big Data has attracted growing attention from academic communities. Concerning the importance of collaboration in scientific research, the current study focused on profiles of collaboration types and size, as well as their relations with citation impact based on publications indexed in the Web of Science (WoS) from 2003 to 2017, so as to provide decision-making basis for optimizing collaboration options. Results show that collaborated publications, as well as collaboration size (i.e., number of authors, institutions and countries) in Big Data have grown substantially. Within-institutional collaboration plays a main role, while international collaboration takes relatively low but rising share. Citation impact is dependent on collaboration types with international collaboration the most efficient, followed by domestic one. None-collaboration receives the least citations. Team size increases over time in general, and is positively related with citation impact, and such phenomenon exists in different collaboration types. Among all the research fields involved, Mathematics and Computer Science is the main contributor in publications and also benefits the most in collaboration despite of its limited team size.