caa a22 4500 445349697 CHVBK 20180317142840.0 cr unu---uuuuu 170323e20111001xx s 000 0 eng 10.1007/s11192-011-0433-7 doi (NATIONALLICENCE)springer-10.1007/s11192-011-0433-7 Mixed-indicators model for identifying emerging research areas [Elektronische Daten] [Hanning Guo, Scott Weingart, Katy Börner] This study presents a mixed model that combines different indicators to describe and predict key structural and dynamic features of emerging research areas. Three indicators are combined: sudden increases in the frequency of specific words; the number and speed by which new authors are attracted to an emerging research area, and changes in the interdisciplinarity of cited references. The mixed model is applied to four emerging research areas: RNAi, Nano, h-Index, and Impact Factor research using papers published in the Proceedings of the National Academy of Sciences of the United States of America (1982-2009) and in Scientometrics (1978-2009). Results are compared in terms of strengths and temporal dynamics. Results show that the indicators are indicative of emerging areas and they exhibit interesting temporal correlations: new authors enter the area first, then the interdisciplinarity of paper references increases, then word bursts occur. All workflows are reported in a manner that supports replication and extension by others. Akadémiai Kiadó, Budapest, Hungary, 2011 Burst detection nationallicence Prediction nationallicence Emerging trend nationallicence Temporal dynamics nationallicence Science of science (Sci2) tool nationallicence Guo Hanning WISE Lab, Dalian University of Technology, Dalian, China aut Weingart Scott Cyberinfrastructure for Network Science Center, School of Library and Information Science, Indiana University, Bloomington, IN, USA aut Börner Katy Cyberinfrastructure for Network Science Center, School of Library and Information Science, Indiana University, Bloomington, IN, USA aut Scientometrics Springer Netherlands 89/1(2011-10-01), 421-435 0138-9130 89:1<421 2011 89 11192 https://doi.org/10.1007/s11192-011-0433-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11192-011-0433-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Guo Hanning WISE Lab, Dalian University of Technology, Dalian, China aut NATIONALLICENCE 700 1- Weingart Scott Cyberinfrastructure for Network Science Center, School of Library and Information Science, Indiana University, Bloomington, IN, USA aut NATIONALLICENCE 700 1- Börner Katy Cyberinfrastructure for Network Science Center, School of Library and Information Science, Indiana University, Bloomington, IN, USA aut NATIONALLICENCE 773 0- Scientometrics Springer Netherlands 89/1(2011-10-01), 421-435 0138-9130 89:1<421 2011 89 11192 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer