E. Kozonogova, Yulia V. Dubrovskaya, M. Rusinova, P. Ivanov
{"title":"ASSESSMENT OF COMPLIANCE OF STRATEGIC DEVELOPMENT PRIORITIES OF REGIONS WITH THEIR INDUSTRY SPECIALIZATION BASED ON TEXT MINING","authors":"E. Kozonogova, Yulia V. Dubrovskaya, M. Rusinova, P. Ivanov","doi":"10.17323/1999-5431-2022-0-2-106-133","DOIUrl":null,"url":null,"abstract":"The task of determining the correctness of self-positioning of regions in terms of verifying the compliance of texts of regional development strategies with their industry specialization was solved in the course of the research presented in the article. Using the \"smart\" benchmarking methodology, as well as the Text Mining tools, long-term development strategies of 11 regions with a total text corpus of 415,780 words were analyzed. The main sections of the all-Russian classifier of economic activities that characterize the sectoral priorities of regional development were selected as keywords. The extraction of key concepts from strategy texts, as well as their quantitative analysis, was carried out using the high-level Python programming language. The obtained quantitative results of comparing the named entities of the development strategies of the subjects of the Russian Federation proved that the insufficiency of unique goal-setting in terms of identifying promising specializations in regional development strategies distorts the system of priority development directions. This is objectively one of the reasons why the territories do not achieve the planned indicators. The paper uses methods of text mining, mathematical statistics, grouping and generalization, as well as techniques for visualizing the analyzed data. The author's method of conducting intellectual analysis of texts is universal for any field of science. The developed algorithms for extracting named entities from the text and algorithms for quantitative analysis of the text open up wide horizons for further research in the field of strategy analysis, as public documents addressed to interested subjects.","PeriodicalId":43338,"journal":{"name":"Voprosy Gosudarstvennogo i Munitsipalnogo Upravleniya-Public Administration Issues","volume":"93 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Voprosy Gosudarstvennogo i Munitsipalnogo Upravleniya-Public Administration Issues","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17323/1999-5431-2022-0-2-106-133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PUBLIC ADMINISTRATION","Score":null,"Total":0}
引用次数: 0
Abstract
The task of determining the correctness of self-positioning of regions in terms of verifying the compliance of texts of regional development strategies with their industry specialization was solved in the course of the research presented in the article. Using the "smart" benchmarking methodology, as well as the Text Mining tools, long-term development strategies of 11 regions with a total text corpus of 415,780 words were analyzed. The main sections of the all-Russian classifier of economic activities that characterize the sectoral priorities of regional development were selected as keywords. The extraction of key concepts from strategy texts, as well as their quantitative analysis, was carried out using the high-level Python programming language. The obtained quantitative results of comparing the named entities of the development strategies of the subjects of the Russian Federation proved that the insufficiency of unique goal-setting in terms of identifying promising specializations in regional development strategies distorts the system of priority development directions. This is objectively one of the reasons why the territories do not achieve the planned indicators. The paper uses methods of text mining, mathematical statistics, grouping and generalization, as well as techniques for visualizing the analyzed data. The author's method of conducting intellectual analysis of texts is universal for any field of science. The developed algorithms for extracting named entities from the text and algorithms for quantitative analysis of the text open up wide horizons for further research in the field of strategy analysis, as public documents addressed to interested subjects.
期刊介绍:
PUBLIC ADMINISTRATION ISSUES is a scientific peer-reviewed journal published by the National Research University High School of Economics (NRU HSE).The journal is published quarterly in Russian, and contains original articles by Russian and foreign authors. In addition, a special English language issue containing original articles by Russian and foreign authors has been published since 2014. The editorial board consists of leading Russian and foreign scientists in the field of public administration as well as prominent practitioners. The journal is indexed in the international databases: Scopus, RePEc, EBSCOand the Russian Science Citation Index (RSCI) on the platform of Web of Science. In addition, the journal is on the list of key peer-reviewed scientific journals and publications that the Higher Certification (Attestation) Commission in the RF Education Ministry recommends for publishing the main scientific results of theses for PhD and doctoral degrees in Economics, Sociology and Law. The journal focuses on the following subject areas: − Current theories of public administration. − Theoretical fundamentals of economic and social policy − Factors and Assessment of efficiency in public and municipal administration. − Innovations in the system of public and municipal administration. − Planning and forecasting in the system of public and municipal administration. − Staff of the state and municipal service. Management of personnel in public and municipal bodies and in organizations of the public sectors. − Financial, logistical and information resources of the state and municipalities. − Public service. − Functional features of public sector organizations. − Partnership of the state and municipalities with nongovernmental nonprofit organizations. Economic and administrative challenges facing “third sector.” - Development of education programs on public administration.