A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

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Keywords automatic term identification, bibliometric mapping, operations research, probabilistic latent semantic analysis, term map
JEL C89, Data Collection and Data Estimation Methodology; Computer Programs: Other (jel), M, Business Administration and Business Economics; Marketing; Accounting (jel), M11, Production Management (jel), R4, Transportation Systems (jel)
Persistent URL hdl.handle.net/1765/19551
van Eck, N.J.P, Waltman, L, Noyons, E.C.M, & Buter, R.K. (2010). Automatic term identification for bibliometric mapping. Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy, 82(3), 581–596. Retrieved from http://hdl.handle.net/1765/19551