Структура российского сообщества экономистов и его отношение к российским экономическим журналам. Ч. 2. Анализ паттернов респондентов
This article is the second part of the study of the Russian economic community on the basis of an analysis of a survey of the Russian economists and its opinion on Russian scientific journals on economics. Patterns characterizing the representation of structure of the Russian economic community were constructed. It turned out that the views of the majority of respondents about the structure of the Russian economic community correspond to their own distribution of working time between teaching at universities, academic research and expert-analytical work. In addition, this distribution also affects economists’ evaluation of scientific journals on economics
New algorithms of patterns analysis based on methods of ordinal-fixed and ordinal-invariant pattern clustering are developed. The definition of the proposed methods as well as the evaluation of the computational complexity is given. We provide some examples that demonstrate features of these clustering procedures and explain their operation. We also formulate and prove the theorem on the interconnection of clusters obtained by the use of ordinal-invariant pattern-clustering with complete weighted digraphs. These results allow to apply graph theory for the study of properties of obtained clusters.
A new method of pattern analysis, based on paired index comparison is introduced. Key properties of the method are described. The effectiveness is demonstrated on the Iris Anderson-Fisher Data.
This paper study the world of education data and patent activity for the period of 1979-2006 years using the latest methods of pattern analysis: a linear pattern-classification and ordinal-invariant pattern clustering. Attempt is made to reflect the situation regarding primary, secondary and higher education in 37 countries.
The work is related to the detection of key international and Russian economic journals in cross-citation networks. A list of international journals and information on their cross-citations were taken from Web of Science (WoS) database while information on Russian journals was taken from Russian Science Citation Index (RSCI). We calculated classical centrality measures, which are used for key elements detection in networks, and proposed new indices based on short-range and long-range interactions. A distinct feature of the proposed methods is that they consider individual attributes of each journal and take into account only the most significant links between them. An analysis of 100 main international and 29 Russian economic journals was conducted. As a result, we detected journals with large number of citations to important journals and also journals where the observed rate of selfcitation is a dominant in the total level of citation. The obtained results can be used as a guidance for researchers planning to publish a new paper and as a measure of importance of scientific journals.
The term “pattern” refers to a combination of values of some features such that objects with these feature values significantly differ from other objects. This concept is a useful tool for the analysis of behavior of objects in both statics and dynamics. If the panel data describing the functioning of objects in time is available, we can analyze pattern changing behavior of the objects and identify either well adapted to the environment objects or objects with unusual and alarming behavior.In this paper we apply static and dynamic pattern analysis to the analysis of innovative development of the Russian regions in the long run and obtain a classification of regions by the similarity of the internal structure of these indicators and groups of regions carrying out similar strategies.