@article{3623,
  author = {Mokhnacheva Yu.V., Tsvetkova V.A},
  title = {Terminological Analysis of Publications as a Method of Research Trends in Science},
  journal = {International Journal of Computational Linguistics Research},
  year = {2022},
  volume = {13},
  number = {4},
  doi = {https://doi.org/10.6025/jcl/2022/13/4/83-87},
  url = {https://www.dline.info/jcl/fulltext/v13n4/jclv13n4_1.pdf},
  abstract = {This article proposes a terminological approach to understanding the dynamics of the development of scientific topics based on the analysis of the sharing of key terms, which is the basis for the development of an algorithm for the distribution of scientific topics into categories: actively developing topics; topics that are in a stable state; topics that are losing relevance or fading away. A hypothesis is proposed that the more keywords with dynamics, greater than 0% in the topic, the higher the probability that this topic is promising and is actively developing. Conversely, the more essential terms in a topic with negative dynamics, the more likely it will indicate the researcher’s interest decreases. The subject area Immunology & Microbiology in SciVal was chosen as a model for studying the dynamics of the development of scientific areas. We assume that if a critical term reduces its usage in one topic, it may appear and grow in other ones. The relevance of various vital terms changes over time for different topics, both in negative and positive dynamics. Using the example of the term “Bibliometric analysis,” the dynamics of this crucial term in other topics are shown.},
}