本文選題：科研社交網(wǎng)絡(luò) + 社會資本��； 參考：《合肥工業(yè)大學》2017年碩士論文

【摘要】：Web 2.0時代,在“互聯(lián)網(wǎng)+”浪潮的帶動下,科研社交網(wǎng)絡(luò)作為知識共享的密集平臺,越來越受到學者們的關(guān)注。我國的科研社交網(wǎng)站還處于起步階段,相較于國外成熟的科研社交網(wǎng)站仍存在一些問題和不足。本文以科學網(wǎng)中管理專業(yè)用戶為研究對象,以互動關(guān)系、個體中心性、信任、共同語言和共同愿景來考察用戶在科研社交網(wǎng)絡(luò)中的社會資本三個維度,同時選擇使用知識共享的數(shù)量和質(zhì)量來評價用戶的知識共享情況,在此基礎(chǔ)上構(gòu)建模型實證探究科研社交網(wǎng)絡(luò)中用戶社會資本對知識共享的影響。通過采用網(wǎng)頁爬蟲技術(shù)自編程序,爬取了科學網(wǎng)中管理專業(yè)2163個用戶數(shù)據(jù),并利用用戶的好友關(guān)系建立網(wǎng)絡(luò),使用R軟件中的“igraph”包計算出個體中心性的相關(guān)指標。經(jīng)過數(shù)據(jù)預(yù)處理和篩選,最終獲得科學網(wǎng)管理專業(yè)439個用戶的樣本數(shù)據(jù),并以上文七個研究變量為出發(fā)點,通過相關(guān)性分析、回歸分析和單因素方差分析得到實證研結(jié)果:個體中心性對知識共享數(shù)量存在顯著正向作用;互動關(guān)系、個體中心性、信任和共同語言對知識共享質(zhì)量存在顯著正向作用;互動關(guān)系、信任、共同語言和共同愿景對知識共享的數(shù)量不存在顯著影響;共同愿景對知識共享質(zhì)量也不存在顯著影響;管理專業(yè)二級學科的不同會引起信任差異;教育程度不會引起本文各研究變量的顯著差異;職稱的不同會引起信任差異;博主身份的不同會引起個體中心性、信任、共同語言和知識共享質(zhì)量的差異。
[Abstract]:In the era of Web 2.0, driven by the tide of "Internet", the scientific research social network as a dense platform for knowledge sharing has been paid more and more attention by scholars. The scientific research social network in our country is still in its infancy, and there are still some problems and shortcomings compared with the mature scientific research social network in foreign countries. This paper takes the professional users of management in ScienceNet as the research object, and examines the three dimensions of social capital of users in the social network of scientific research in terms of interaction, individual centrality, trust, common language and common vision. At the same time, we choose to use the quantity and quality of knowledge sharing to evaluate the knowledge sharing of users, and then build a model to explore the impact of social capital of users on knowledge sharing in scientific research social networks. By using the web crawler technique, 2163 users' data of management specialty in the scientific network were crawled, and the network was established by using the user's friend relationship, and the relevant index of individual centrality was calculated by using the "igraph" package in R software. After data preprocessing and screening, the sample data of 439 users of the science network management specialty were obtained, and based on the seven research variables above, the correlation analysis was carried out. Regression analysis and univariate ANOVA show that: individual centrality has a significant positive effect on the quantity of knowledge sharing, interaction, individual centrality, trust and common language have significant positive effects on the quality of knowledge sharing. Interaction, trust, common language and common vision have no significant influence on the quantity of knowledge sharing, shared vision has no significant influence on the quality of knowledge sharing, the difference of management subject will cause the difference of trust. Education level will not lead to significant differences in the study variables; different titles will lead to differences in trust; different identities of bloggers will lead to individual centrality, trust, common language and knowledge sharing quality differences.
【學位授予單位】：合肥工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP393.09;G203

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