Research On Knowledge Flow Network Of Chinese Oil And Gas Industry Based On Published Papers

For a long time, in order to guide oil and gas production, practitioners of oil and gas industry in China have done a lot of innovative research and practical work, which have made tremendous contributions to the development of the industry and national energy security. Over time, these findings have accumulated into forming a lot of "big data" libraries which are distributed in all aspects of the industry, but the value of these data has not been fully mined. To solve this problem, based on the large data flow theory and the theory of knowledge, this thesis combined with knowledge of metrology, software engineering, statistics, econometrics, social network analysis, visualization of knowledge and management, mined deeply literature related the study of knowledge flow and literature related Chinese oil and gas industry, made analysis of the progress of knowledge flow, the frontier of this thesis, the relationship between the number of scientific achievements and performance of Chinese oil and gas industry, the distribution of research hotspots of Chinese oil and gas industry, the distribution and collaborative status of researchers in Chinese oil and gas industry research and the distribution and collaborative status of institutes Chinese oil and gas industry, explored and revealed the knowledge flow network in Chinese oil and gas industry from multiple perspectives, to provide intellectual support for collaborative research networks in Chinese oil and gas industry and decision support to achieve innovation-driven development of Chinese oil and gas industry. In this regard, this thesis carried out following researches:Firstly, based on CNKI database and WOS database, used the method of literature review and social network analysis to deeply analyze the research status of Chinese and foreign knowledge flow, constructed Chinese and foreign knowledge flow research hotspots network to analyze by the near synonyms co-occurrence principle, demonstrated the topic of this thesis frontier and scientific, summarized the main content, method and development tendency of knowledge flow network research.Secondly, this thesis made empirical analysis to demonstrate relation between the number of research papers related to Chinese oil and gas industry in CNKI database and the oil and gas production data in Chinese National Statistical Yearbook over the years. Calculation and analysis showed that the correlation coefficient between the number of various research papers and oil and gas production of the industry was higher than 0.88, there is a deterministic cointegration relationship between the number of CSCD core papers of the industry and oil and gas production of the industry, which laid a good foundation of research on knowledge flow network of Chinese oil and gas industry.Thirdly, based on the theory of big data, using the software engineering knowledge to to get keywords data related to oil and gas industry, constructed knowledge flow network of oil and gas industry from its keywords of all papers, keywords of core papers, time dimension, adopted the method of frequency analysis and social network analysis to analyze it, and visualized analysis the conclusions. It is concluded that the keywords' distribution of oil and gas industry presents "two-eight" rule, researchers pay more attention to the application of research results and geological research, the focus of the researches is in the sedimentary basin of the Midwest China, and the research of Marine oil and gas development is relatively lacking,etc.Fourthly, based on big data theory, this thesis used software to obtain authors'and institutes'data of Chinese oil and gas industry and make analysis on distributed status of authors' cliques in Chinese oil and gas industry, constructed authors (institutes)" co-occurrence network based on authors (institutes)'co-occurrence network and used Lorenz curve, Gini coefficient, frequency analysis and social network analysis method to analyze it, and visualized the research results. It is concluded that the gini coefficient of researcher" productions is 0.35, the core network is divided by multiple factions, petroleum colleges and universities play an important roles in it, and the cliques of the networks show strong regional characteristics,etc.Fifth, based on big data theory, the paper used software to obtain institutes data of Chinese oil and gas industry and make analysis on distributed status of institutes'cliques in Chinese oil and gas industry, constructed institutes'distribution and institutes'co-occurrence distribution and deeply analyze their distribution and ranking, used cluster analysis of social network analysis to reveal core cliques in knowledge flow network of Chinese oil and gas industry, discussed structural features inherent core network of institutions combined with development history of Chinese oil and gas industry and knowledge of human geography, and visualized the research results. It is concluded that the level of synergistic proportion is rather low, the innovative output distributions of institutions nearly obey to power law, petroleum colleges and universities are at the center of the knowledge flow of Chinese oil and gas industry, and the scope of services of scientific institutions shows strong regional effects, etc.Sixth, on the basis of various chapters" research, summarized research findings of each part, provided suggestions to optimize knowledge flow network in Chinese oil and gas industry and analyzed the innovation, limitations and research prospects of this thesis.In a word, this thesis absorbed some theory of big data and knowledge, took scientific papers related with Chinese oil and gas industry as object, used frequency analysis and social network analysis to deeply mined knowledge flow network of Chinese oil and gas industry from multiple perspective based on the characteristics of literature, got a lot of valuable results, which can provide intelligent support for the development of Chinese oil and gas industry and a generally analyzed framework to other industries to create more large social value.