Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks

• Published in: Scientometrics Vol. 101; no. 2; pp. 1253 - 1271
• Main Authors: Wang, Xiaoguang, Cheng, Qikai, Lu, Wei
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Dordrecht Springer Netherlands 01.11.2014; Springer
• Subjects: Bibliometrics. Scientometrics; Bibliometrics. Scientometrics. Evaluation; Computer Science; Detection; Exact sciences and technology; Information and communication sciences; Information science. Documentation; Information Storage and Retrieval; Library and information science. General aspects; Library Science; Methods; Sciences and techniques of general use; Subject fields; Trends; Co-word analysis; Topic evolution; Network communities; Science mapping; Emerging trend detection; Scientific research; Algorithm; Cooccurrence analysis; Coword analysis; Coword

Understanding the evolution of research topics is crucial to detect emerging trends in science. This paper proposes a new approach and a framework to discover the evolution of topics based on dynamic co-word networks and communities within them. The NEViewer software was developed according to this...