The State of Synthetic Biology Scholarship: A Case Study of Comparative Metrics and Citation Analysis

This chapter explores the current state of synthetic biology by applying a network/connectivity analysis to publications within the field in order to better understand the different disciplines and actors evaluating synthetic biology and where they are headed. Seven hundred twelve publications were identified through the Web of Science database, and a citation network was built through a text mining process in R. Each publication is classified based on its community of practice as either a (1) state of science, (2) products, (3) risk, (4) governance, or (5) ethical, legal, and social implications (ELSI), and interrelationships were identified across each community of practice. Then, centrality measures of indegree, outdegree, betweenness, and eigencentrality were calculated to show important and seminal nodes. Finally, the centrality measures were analyzed over time to determine critical publications within the citation network. The results show that state of science has the largest share of cited publications within each community of practice. Also, the network’s indegree centrality is highly correlated with eigencentrality, indicating that the most cited publications are also the ones that are connected to other highly cited publications. Furthermore, this chapter demonstrates that text mining is an applicable tool to extract references from publications, construct a citation network, and understand the structure of an emerging body of literature.