本文選題：大數(shù)據(jù) + 知識擴(kuò)散　； 參考：《南京信息工程大學(xué)》2017年碩士論文

【摘要】：知識生產(chǎn)的關(guān)鍵環(huán)節(jié)是知識擴(kuò)散,在知識的傳承與創(chuàng)新中具有重要作用。在當(dāng)今大數(shù)據(jù)時代,科研機(jī)構(gòu)對此領(lǐng)域開展研究,涌現(xiàn)了大量優(yōu)秀的科研成果,在這一背景下,本研究以WOS核心合集中大數(shù)據(jù)研究領(lǐng)域的文章作為數(shù)據(jù)源,從學(xué)科、作者、關(guān)鍵詞這3個維度來探究國外此研究領(lǐng)域知識擴(kuò)散的特征;以知網(wǎng)中CSSCI期刊的大數(shù)據(jù)領(lǐng)域論文為研究對象,從學(xué)科、期刊、機(jī)構(gòu)、關(guān)鍵詞這四個層面探索國內(nèi)社科領(lǐng)域大數(shù)據(jù)研究的知識擴(kuò)散特征。論文從強(qiáng)度和廣度這兩個維度,對以學(xué)科作為主體的知識擴(kuò)散進(jìn)行了測量;構(gòu)建了作者合作網(wǎng)絡(luò)、期刊引用網(wǎng)絡(luò)、機(jī)構(gòu)引用網(wǎng)絡(luò)、關(guān)鍵詞共現(xiàn)網(wǎng)絡(luò),運(yùn)用工具Ucinet從密度、中心性、凝聚子群分析、核心-邊緣結(jié)構(gòu)分析進(jìn)行探究,并借助Netdraw通過圖形進(jìn)一步形象展示。通過對國外大數(shù)據(jù)研究領(lǐng)域知識擴(kuò)散特征的探討,從學(xué)科看,知識擴(kuò)散廣度呈現(xiàn)相對穩(wěn)定特征;從研究作者合作看,知識擴(kuò)散呈現(xiàn)相對封閉的特征;從研究熱點來看,呈現(xiàn)節(jié)點集聚的特征。闡述國內(nèi)社科領(lǐng)域大數(shù)據(jù)研究知識擴(kuò)散特征,知識擴(kuò)散廣度呈現(xiàn)出現(xiàn)奇點之后相對穩(wěn)定的特征;從期刊互引和機(jī)構(gòu)互引上來看,呈現(xiàn)知識擴(kuò)散相對封閉的特征;從研究主題來看,知識擴(kuò)散節(jié)點較集中。整體而言,大數(shù)據(jù)研究是新興領(lǐng)域,相關(guān)主體應(yīng)加強(qiáng)交流,了解各自的研究動態(tài),推進(jìn)知識擴(kuò)散,促進(jìn)知識利用效率的提高。
[Abstract]:The key link of knowledge production is knowledge diffusion, which plays an important role in knowledge inheritance and innovation. In the era of big data, scientific research institutions have carried out research in this field, and a large number of excellent scientific research results have emerged. Under this background, this study takes the articles in the field of large data research in the core collection of WOS as the data source, from the subject, the author, These three dimensions are to explore the characteristics of knowledge diffusion in this field of research abroad, and take the big data field papers of CSSCI journals in the knowledge network as the research object, from the subject, the journal, the institution, These four levels explore the characteristics of knowledge diffusion in big data research in the field of social sciences in China. This paper measures the knowledge diffusion with the subject as the main body from the two dimensions of intensity and breadth, constructs the author's cooperative network, the periodical citation network, the institutional citation network, the keyword co-occurrence network, and applies the tool Ucinet to the density. Centrality, condensed subgroup analysis, core-edge structure analysis, and Netdraw through graphics to further image display. Through the discussion of the characteristics of knowledge diffusion in the field of big data research abroad, from the perspective of discipline, the breadth of knowledge diffusion presents a relatively stable feature; from the point of view of the authors' cooperation, knowledge diffusion presents a relatively closed feature; from the point of view of the research hotspot, the knowledge diffusion presents a relatively closed feature. It presents the characteristics of node agglomeration. This paper expounds the characteristics of knowledge diffusion in big data research in the field of social sciences in China, which shows that the breadth of knowledge diffusion is relatively stable after the emergence of singularities, and that the knowledge diffusion is relatively closed in terms of journal citation and institutional citation. From the point of view of the research topic, knowledge diffusion nodes are more concentrated. As a whole, big data research is a new field. The relevant subjects should strengthen communication, understand their research trends, promote knowledge diffusion and promote the efficiency of knowledge utilization.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：G201;F49

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