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.

Additional Metadata
Keywords Automatic term identification, Bibliometric mapping, Operations research, Probabilistic latent semantic analysis, Term map
Persistent URL dx.doi.org/10.1007/s11192-010-0173-0, hdl.handle.net/1765/19808
Citation
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. doi:10.1007/s11192-010-0173-0