社交網絡數據獲取與結構分析系統(tǒng)的設計與實現(xiàn)
發(fā)布時間：2018-07-29 14:04
【摘要】：Web2.0時代的到來,使得互聯(lián)網技術朝著更加人性化的方式發(fā)展,Twitter、 Facebook、微博、朋友網、人人網等社交軟件也隨之興起并飛速發(fā)展,目前,人們的日常交流活動基本都是在這些社交軟件所提供的平臺上進行。人與人之間以這些社交軟件為媒介進行有目的的信息交流,從而產生關系網絡,這種以人,和人與人之間關系而構成的社會網絡結構,稱之為社交網絡。社交網絡的兩個結構要素是節(jié)點和邊,節(jié)點一般指人,邊是人與人之間的關系。順應科技發(fā)展的需要而產生的科研合作網絡,是科研合作的產物,是科研學者之間的社交網絡,而科研合著網絡又是科研合作網絡中由科研學者之間通過合著論文而產生關系從而構成的合著者之間的社交網絡。本文研究的對象為社交網絡中有代表性的兩種網絡：微博用戶關系網絡和科研合著網絡,前者是有向網絡,后者是無向網絡。 社交網絡的概念來源于社會學,自提出以來就引起了國內外學者的廣泛關注,到目前為止,社交網絡的研究熱潮仍未退去。網絡數據的獲取是社交網絡研究所要解決的首要問題,但是,大多數已有的關于社交網絡的研究,其網絡數據來源是公用數據集,或者模擬的網絡數據集,這在一定程度上不能準確地反映社交網絡結構的真實情況。所以,從互聯(lián)網上獲取真實的社交網絡結構數據就顯示尤為重要,也使得社交網絡的研究成果更加具有實際意義。本文設計的社交網絡數據獲取與結構分析系統(tǒng)實現(xiàn)了真實數據的獲取,分別從新浪微博系統(tǒng)和DBLP數據庫中獲取真實的新浪微博用戶關系數據與合著關系數據。 社會網絡分析方法和復雜網絡分析方法是被國內外學者廣泛認可的兩種社交網絡結構分析方法。對于科研合著網絡來說,分析其網絡結構,對促進科研合作的繼續(xù)發(fā)展,預測某一領域的發(fā)展方向等具有重要的作用。對于微博用戶關系網而言,分析其網絡結構,對于市場運營、用戶推薦等都有著重要的借鑒意義。本文設計并實現(xiàn)的系統(tǒng)采用社會網絡分析方法中的角色分析方法研究科研合著網絡結構,對意見領袖和結構洞進行分析研究,采用復雜網絡分析方法研究新浪微博用戶關系網絡的拓撲結構特性。 本文設計并實現(xiàn)了社交網絡數據獲取與網絡結構分析系統(tǒng),主要工作如下： 1、介紹了本文在設計并實現(xiàn)系統(tǒng)時涉及到的相關概念和技術。 2、設計并實現(xiàn)新浪微博數據獲取與網絡結構分析功能,使系統(tǒng)可以完成從新浪微博系統(tǒng)中獲取真實的用戶關系數據,對數據進行去噪處理,并生成關系網絡結構圖,且采用復雜網絡分析方法對網絡拓撲結構特性進行分析等一系列工作。 3、設計并實現(xiàn)科研合著網絡數據獲取與結構分析功能,使系統(tǒng)可以完成從DBLP數據庫中獲取以“數據挖掘”為主題的四個級別的學術會議收錄的論文合著數據,對數據進行處理,生成合著網絡結構圖,檢測出top100個結構洞和意見領袖等功能。 4、以top100個結構洞和意見領袖為研究對象,分別從論文數、citation number、H-index和G-index這四種衡量科研學者學術成就的重要指標進行對比分析。
[Abstract]:The arrival of the Web2.0 era makes Internet technology develop towards a more humanized way. Social software, such as Twitter, Facebook, micro-blog, friend network and Renren network, has also developed and developed rapidly. At present, people's daily communication activities are basically on the platform provided by these social software. The two structural elements of a social network are nodes and sides, the nodes are generally people and the relationship between people and people. They are generated by the needs of the development of science and technology. The research cooperation network is the product of scientific research cooperation, the social network among scientific researchers, and the scientific research collaboration network is the social network between the co authors of scientific research cooperation network which is formed by the co authored papers among the scientific researchers. The object of this paper is the two kinds of representative networks in the social network: micro network. Bo user relationship network and research coauthor network. The former is directed network while the latter is undirected network.
The concept of social network comes from sociology, which has aroused wide attention of scholars at home and abroad since it was put forward. So far, the research upsurge of social network has not been retreated. The acquisition of network data is the primary problem to be solved by social network research institute. However, most of the research on social networks, its network data sources It is a public data set, or a simulated network data set, which can not accurately reflect the real situation of the social network structure. Therefore, it is particularly important to obtain real social network structure data from the Internet, and make the research results of social networks more practical. The social network designed in this paper The data acquisition and structural analysis system realized the acquisition of real data, and obtained real Sina micro-blog user relations data and co authored data from Sina micro-blog system and DBLP database.
The social network analysis method and the complex network analysis method are two social network structure analysis methods widely recognized by the domestic and foreign scholars. For the scientific research collaboration network, the analysis of its network structure plays an important role in promoting the continuous development of scientific research cooperation and predicting the direction of the development of a certain field. For the micro-blog user relations network For the analysis of its network structure, it is of great significance for market operation and user recommendation. The system used in this paper is designed and implemented by the role analysis method in the social network analysis method to study the cooperative network structure, analyze the opinion leader and the structure hole, and study the Sina with complex network analysis method. The topology of the micro-blog user relationship network.
This paper designs and implements a data acquisition and network structure analysis system for social networks. The main tasks are as follows:
1, introduce the related concepts and technologies involved in the design and implementation of the system.
2, the design and implementation of sina micro-blog data acquisition and network structure analysis function, so that the system can complete the real user relationship data from the Sina micro-blog system, denoise the data, and generate a relational network structure diagram, and use the complex network analysis method to analyze the network topology characteristics and so on a series of work.
3, design and implement the function of data acquisition and structure analysis of the joint research network, so that the system can complete the data collected from the four academic conferences of "data mining" from the DBLP database, process the data, generate the co authored network composition, detect the Top100 structure holes and opinion leaders, etc. Function.
4, with Top100 structure holes and opinion leaders as the research object, the paper compares the four important indexes of academic achievements of scientific research scholars from the number of papers, citation number, H-index and G-index, respectively.
【學位授予單位】：安徽大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.09
本文編號：2152910
[Abstract]:The arrival of the Web2.0 era makes Internet technology develop towards a more humanized way. Social software, such as Twitter, Facebook, micro-blog, friend network and Renren network, has also developed and developed rapidly. At present, people's daily communication activities are basically on the platform provided by these social software. The two structural elements of a social network are nodes and sides, the nodes are generally people and the relationship between people and people. They are generated by the needs of the development of science and technology. The research cooperation network is the product of scientific research cooperation, the social network among scientific researchers, and the scientific research collaboration network is the social network between the co authors of scientific research cooperation network which is formed by the co authored papers among the scientific researchers. The object of this paper is the two kinds of representative networks in the social network: micro network. Bo user relationship network and research coauthor network. The former is directed network while the latter is undirected network.
The concept of social network comes from sociology, which has aroused wide attention of scholars at home and abroad since it was put forward. So far, the research upsurge of social network has not been retreated. The acquisition of network data is the primary problem to be solved by social network research institute. However, most of the research on social networks, its network data sources It is a public data set, or a simulated network data set, which can not accurately reflect the real situation of the social network structure. Therefore, it is particularly important to obtain real social network structure data from the Internet, and make the research results of social networks more practical. The social network designed in this paper The data acquisition and structural analysis system realized the acquisition of real data, and obtained real Sina micro-blog user relations data and co authored data from Sina micro-blog system and DBLP database.
The social network analysis method and the complex network analysis method are two social network structure analysis methods widely recognized by the domestic and foreign scholars. For the scientific research collaboration network, the analysis of its network structure plays an important role in promoting the continuous development of scientific research cooperation and predicting the direction of the development of a certain field. For the micro-blog user relations network For the analysis of its network structure, it is of great significance for market operation and user recommendation. The system used in this paper is designed and implemented by the role analysis method in the social network analysis method to study the cooperative network structure, analyze the opinion leader and the structure hole, and study the Sina with complex network analysis method. The topology of the micro-blog user relationship network.
This paper designs and implements a data acquisition and network structure analysis system for social networks. The main tasks are as follows:
1, introduce the related concepts and technologies involved in the design and implementation of the system.
2, the design and implementation of sina micro-blog data acquisition and network structure analysis function, so that the system can complete the real user relationship data from the Sina micro-blog system, denoise the data, and generate a relational network structure diagram, and use the complex network analysis method to analyze the network topology characteristics and so on a series of work.
3, design and implement the function of data acquisition and structure analysis of the joint research network, so that the system can complete the data collected from the four academic conferences of "data mining" from the DBLP database, process the data, generate the co authored network composition, detect the Top100 structure holes and opinion leaders, etc. Function.
4, with Top100 structure holes and opinion leaders as the research object, the paper compares the four important indexes of academic achievements of scientific research scholars from the number of papers, citation number, H-index and G-index, respectively.
【學位授予單位】：安徽大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.09
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