【摘要】：社會網(wǎng)絡(luò)結(jié)構(gòu)建模是社會網(wǎng)絡(luò)其它領(lǐng)域研究的基礎(chǔ),旨在構(gòu)建合理的社會網(wǎng)絡(luò)結(jié)構(gòu)模型。但由于隱私保護等諸多原因,幾乎不可能獲取構(gòu)建社會網(wǎng)絡(luò)結(jié)構(gòu)模型所需的全部數(shù)據(jù),因此研究利用不完整數(shù)據(jù)構(gòu)建社會網(wǎng)絡(luò)結(jié)構(gòu)模型十分必要。現(xiàn)有的構(gòu)建社會網(wǎng)絡(luò)結(jié)構(gòu)模型的方法雖然有許多,但都存在一定的問題,比如早期的靜態(tài)模型并不具有社會網(wǎng)絡(luò)的全部拓撲特性,大部分的動態(tài)模型中節(jié)點隨時間推進無限增長。本文首先從應用場景分析出發(fā),提煉技術(shù)需求,然后分別從時間、空間以及時空融合三個不同角度,設(shè)計了三種社會網(wǎng)絡(luò)結(jié)構(gòu)模型——基于歷史事件的自然生長模型、基于局部網(wǎng)絡(luò)信息的重構(gòu)模型以及時空融合社會網(wǎng)絡(luò)模型�；跉v史事件的自然生長模型是一種基于行為原則以及事件對網(wǎng)絡(luò)結(jié)構(gòu)影響機制的動態(tài)模型;基于局部網(wǎng)絡(luò)信息的重構(gòu)模型建立在修正的共鄰相似性和屬性相似性兩種鏈路預測指標之上;時空融合社會網(wǎng)絡(luò)模型的構(gòu)建則結(jié)合了社會網(wǎng)絡(luò)自然選擇等基礎(chǔ)理論�；贜etlogo實驗平臺,本文使用不同的實驗數(shù)據(jù)及方法,對上述三種網(wǎng)絡(luò)模型進行了實驗驗證。實驗證明,三種網(wǎng)絡(luò)模型分別在不同條件下具有較好的準確性。因此,具體應用場景下,可以根據(jù)可獲取數(shù)據(jù)的不同,選擇相應的模型建立社會網(wǎng)絡(luò)結(jié)構(gòu)。此外,由于外在環(huán)境和節(jié)點自身狀態(tài)的不斷變化,社會網(wǎng)絡(luò)的結(jié)構(gòu)也隨之不斷變化,但社會網(wǎng)絡(luò)的這種變化總是使其結(jié)構(gòu)在整體上向著更加穩(wěn)定的方向發(fā)展。
[Abstract]:The modeling of social network structure is the basis of other fields of social network research, aiming at constructing a reasonable social network structure model. However, for many reasons, such as privacy protection, it is almost impossible to obtain all the data needed to construct the social network structure model, so it is very necessary to study the use of incomplete data to construct the social network structure model. Although there are many existing methods of constructing social network model, there are some problems. For example, the early static model does not have all the topological characteristics of social network. In most dynamic models, nodes grow infinitely with time. In this paper, first of all, from the perspective of application scenario analysis, we refine the technical requirements, and then from three different angles of time, space and space fusion, we design three kinds of social network structure models-natural growth model based on historical events. Reconstruction model based on local network information and spatiotemporal fusion social network model. The natural growth model based on historical events is a dynamic model based on behavior principle and the influence mechanism of event on network structure. The reconstruction model based on local network information is based on two kinds of link prediction indexes: the modified co-neighbor similarity and attribute similarity, while the space-time fusion social network model combines the basic theories of social network natural selection and so on. Based on the Netlogo experimental platform, this paper uses different experimental data and methods to verify the above three network models. Experiments show that the three network models have better accuracy under different conditions. Therefore, according to the difference of available data, the corresponding model can be selected to establish the social network structure in the specific application scenario. In addition, the structure of social network changes with the change of external environment and the state of node itself, but the change of social network always makes the structure of social network more stable as a whole.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O157.5

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