本文關(guān)鍵詞：社交網(wǎng)絡(luò)中的信息與影響力傳播模式研究　出處：《北京交通大學(xué)》2017年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 社交網(wǎng)絡(luò) 信息傳播 影響力傳播最大化 信息干擾 節(jié)點影響力

【摘要】：在當(dāng)今互聯(lián)網(wǎng)絡(luò)時代大背景下,電視、廣播、報紙等曾經(jīng)主流媒體的地位正逐漸降低,而具有便捷性、實時性、低門檻等特點的網(wǎng)絡(luò)媒體開始活躍起來。社交網(wǎng)絡(luò)作為網(wǎng)絡(luò)媒體的載體,在融合了社交娛樂、新聞傳播、信息推廣等多種元素的情況下,成為了人們接通外界過程中不可或缺的一扇窗戶,也正是由于社交網(wǎng)絡(luò)綜合性強、結(jié)構(gòu)錯綜復(fù)雜等特點,使得社交網(wǎng)路中的輿論相比于傳統(tǒng)的輿論更加的復(fù)雜。不同社會群體間信息傳遞更加頻繁,個體間的交互模式、參與話題及信息的方式更加多樣化,而傳統(tǒng)的輿論研究較難適用于上述的新環(huán)境。因此,探索社交網(wǎng)絡(luò)信息傳播規(guī)律、個體交互模式、特征差異性分析等問題的必要性日益凸顯:研究需要從不同的角度分析用戶行為,更為細(xì)致的刻畫信息交互規(guī)律,比如不同情境下的用戶決策行為模式和交互模型,同時,需要結(jié)合影響力與影響范圍的分析,從社交網(wǎng)絡(luò)的復(fù)雜交互情境入手,研究信息競爭與信息價值的內(nèi)在關(guān)系。鑒于此,本文從多學(xué)科交叉的角度,采用實證數(shù)據(jù)分析、數(shù)學(xué)建模和計算機仿真相結(jié)合的研究方法,圍繞社交網(wǎng)絡(luò)中信息與影響力的傳播規(guī)律,對社交網(wǎng)絡(luò)中的信息傳播過程、信息干擾與競爭傳播模式、用戶影響力分析和影響力傳播最大化等問題進行了深入的探索。本研究不僅能夠幫助相關(guān)研究者加深對復(fù)雜網(wǎng)絡(luò)研究和影響力問題的認(rèn)識,豐富社交網(wǎng)絡(luò)中個體交互行為演化和信息傳播等方面的理論,而且能夠為解決實際問題提供有效的幫助。論文的研究工作得到了國家自然科學(xué)基金項目(No.61271308、No.61401015)、北京市重點實驗室資助項目和北京市重點學(xué)科建設(shè)項目等項目的支持。論文的主要工作和創(chuàng)新點如下:1.內(nèi)容可靠性是信息的重要特征屬性,然而,在大多數(shù)社交網(wǎng)絡(luò)信息傳播研究中,缺乏對可靠性因素的系統(tǒng)建模與分析。研究結(jié)合了社交網(wǎng)絡(luò)用戶行為的主觀性特點,分析了內(nèi)容可靠性因素的作用機理,并根據(jù)社交網(wǎng)絡(luò)信息的實際交互情景,提出了用戶的反饋勸說機制,建立了基于內(nèi)容可靠性因素的信息傳播模型。通過建立平均場速率模型,并結(jié)合蒙特卡洛仿真實驗,分析了用戶對信息可靠性的懷疑程度與信息實際傳播結(jié)果之間關(guān)系,并分析了在不同網(wǎng)絡(luò)結(jié)構(gòu)中可靠性影響的差異。仿真結(jié)果發(fā)現(xiàn):信息內(nèi)容可靠性因素對信息傳播的實際結(jié)果起到?jīng)Q定性作用,用戶對信息可靠性的懷疑程度顯著影響著信息傳播范圍、傳播速度、傳播閾值、傳播周期,而且該影響對網(wǎng)絡(luò)疏密程度的依賴性較低;此外,發(fā)現(xiàn)信息傳播的實際影響力為用戶對信息內(nèi)容可靠性的認(rèn)可度,實際影響力的傳播范圍遠(yuǎn)小于信息的擴散范圍。研究社交網(wǎng)絡(luò)信息傳播研究中加入信息內(nèi)容可靠性因素,能夠加深對信息傳播動力的認(rèn)識,豐富復(fù)雜網(wǎng)絡(luò)理論,為探索社交網(wǎng)絡(luò)信息傳播及演化規(guī)律提供了有效的幫助。2.衍生信息傳播干擾在社交網(wǎng)絡(luò)信息傳播過程中普遍存在,而傳統(tǒng)的信息干擾模型僅從宏觀角度分析信息傳播及作用關(guān)系,缺乏對社交網(wǎng)絡(luò)用戶交互行為的微觀刻畫。根據(jù)社交網(wǎng)絡(luò)用戶與信息的交互特點,分析了衍生信息的產(chǎn)生條件、共存?zhèn)鞑ツＪ健⒂脩襞c二元信息交互規(guī)則,并結(jié)合多元信息模型與社交強化理論,建立了一種基于衍生信息干擾的二元傳播模型,針對衍生干擾現(xiàn)象,提出了先驗干擾態(tài)與后驗干擾態(tài)的概念,構(gòu)建了二元社交強化規(guī)則,成功的將單信息模型中用戶一維狀態(tài)轉(zhuǎn)化關(guān)系的擴展為二維狀態(tài)轉(zhuǎn)化關(guān)系。研究分析了基于衍生信息干擾的二元信息傳播規(guī)律,并在規(guī)則網(wǎng)絡(luò)與隨機網(wǎng)絡(luò)中進行了對比分析。實驗結(jié)果表明:衍生干擾情況下的用戶轉(zhuǎn)發(fā)行為存在明顯的"先入為主"現(xiàn)象,且干擾形式主要為后驗干擾;此外,發(fā)現(xiàn)規(guī)則網(wǎng)絡(luò)對信息干擾的時效性門檻要求比隨機網(wǎng)絡(luò)要低,這就表明規(guī)則網(wǎng)絡(luò)下的信息傳播更容易受到衍生干擾。研究衍生信息干擾現(xiàn)象與建模,有助理解社交網(wǎng)絡(luò)多元傳播模式中的網(wǎng)絡(luò)干預(yù)現(xiàn)象,為信息干擾傳播的研究提供新的研究思路,具有較高理論價值和實際意義。3.個體影響力分析是信息傳播理論中個體異質(zhì)性研究的最主要部分,效率與精度的權(quán)衡一直是社交網(wǎng)絡(luò)個體影響力排序算法最主要問題。研究在社交網(wǎng)絡(luò)拓?fù)涮卣鞯幕A(chǔ)上,利用網(wǎng)絡(luò)結(jié)構(gòu)中影響力的傳遞特性,以節(jié)點中心性和權(quán)威性描述節(jié)點的影響力,并以中樞節(jié)點的連通性為核心,提出了關(guān)于社交網(wǎng)絡(luò)節(jié)點影響力的迭代加權(quán)指標(biāo)IEW(Iterative Equalization Weight)。研究分別采用皮爾遜系數(shù)相關(guān)性和網(wǎng)絡(luò)魯棒性分析方法,對比了 IEW指標(biāo)與其他三類經(jīng)典算法的優(yōu)劣,并在真實網(wǎng)絡(luò)數(shù)據(jù)集中采用信息傳播動力學(xué)模型進行實際驗證。驗證結(jié)果表明:相比于傳統(tǒng)算法,IEW通過犧牲一定運算速度獲得了更高的準(zhǔn)確性,并且算法的可靠性較有明顯提高。研究提出的新算法為挖掘高效、可靠、準(zhǔn)確的社交網(wǎng)絡(luò)節(jié)點影響力評估算法提供了新思路,對深入研究社交網(wǎng)絡(luò)信息與影響力傳播規(guī)律起到理論支持作用。4.多節(jié)點的影響力傳播最大化問題是結(jié)合信息傳播理論與節(jié)點影響力分析的實際問題,傳統(tǒng)算法難以根據(jù)實際需求靈活的調(diào)節(jié)算法的復(fù)雜度,并且算法可擴展性普遍較低。研究根據(jù)社交網(wǎng)絡(luò)節(jié)點度冪律分布特性,分析并結(jié)合了貪心算法與啟發(fā)式算法優(yōu)缺點,提出了基于最優(yōu)鄰居發(fā)現(xiàn)的社交網(wǎng)絡(luò)節(jié)點影響力最大化算法MNH(Max Neighbor Heuristic),該算法通過隨機啟發(fā)來構(gòu)建貪心候選節(jié)點集,再利用計算節(jié)點邊際增益的方式,近似估計最大影響力節(jié)點集合,實現(xiàn)了效率與精度的互換與調(diào)節(jié)。研究利用數(shù)學(xué)推導(dǎo)和理論證明的方式驗證了算法的可行性和精確性,并在真實網(wǎng)絡(luò)數(shù)據(jù)集中進行了蒙特卡洛仿真實驗,利用獨立級聯(lián)傳播模型與線性閾值傳播模型,驗證和對比了 MNH算法與其他三類經(jīng)典算法的優(yōu)劣。分析結(jié)果表明:雖然MNH算法的求解結(jié)果存在較為明顯的波動性,但在算法平均耗時與精確度的綜合分析上具有明顯優(yōu)勢,并且表現(xiàn)出更高的可適性。研究較好的結(jié)合了啟發(fā)式算法和貪心式算法的優(yōu)點,為解決社交網(wǎng)絡(luò)多節(jié)點傳播影響力最大化問題的提供新方法與思路,是利用信息傳播理論解決實際問題的一次有效嘗試,具有較好的實際意義。
[Abstract]:In today's Internet era background, television, radio, newspapers and other mainstream media once status is gradually reduced, which is convenient, real-time, low threshold and other characteristics of the network media began to perk up. Social network as the carrier of the network media, the dissemination of news in the integration of social entertainment, information, promotion etc. elements of the case, to become the people on the outside of an integral part of the window, it is also due to the social network comprehensive structure, perplexing characteristics, makes social network public opinion compared to the traditional public opinion is more complex. Information transmission between different social groups more frequently, interaction between individuals, participation the topic and the way information is more diversified, and the traditional public opinion research is hard to apply to the new environment. Therefore, exploring the propagation rules of social network information, individual special interaction model. The necessity of syndrome differential analysis has become increasingly prominent problems such as: Study of user behavior analysis from different angles, more detailed characterization of the information exchange rules, such as the different situations user decision behavior model and interactive model, at the same time, it should be combined with the analysis of influence and impact range, starting from the complex situation of interactive social network study on the relationship between information, internal competition and the value of information. In view of this, this article from the multidisciplinary perspective, using empirical research methods of data analysis, mathematical modeling and computer simulation of combining the propagation and influence of information on social networks, the information dissemination process in social network, information interference and competition mode of transmission and probe into the influence of user analysis and the influence of the spread of the maximum problem. This study can not only help researchers deepen our understanding of the complex network Understanding of the problem and influence, rich individual behavior in social network evolution and dissemination of information theory, and can provide effective help for solving practical problems. The research work of this thesis is supported by the National Natural Science Fund Project (No.61271308, No.61401015), supported by the Key Laboratory of Beijing city and Beijing city key project project support. The main work and innovation are as follows: 1. the content of reliability is an important attribute of information, however, in most of the social network information dissemination, lack of system modeling and analysis of the reliability factors. Based on the subjective characteristics of social network user behavior, analyzes the mechanism of content reliability factors and, according to the information of the actual social network interaction scenarios, proposes the user feedback mechanism is built based on persuasion, content Rely on the information dissemination model of factors. Through the establishment of the mean field rate model and Monte Carlo simulation, to analyze the relationship between the actual dissemination of results and information users suspected degree of reliability of information, and analyzes on the different network structure influences the reliability of difference. The simulation results showed that play a decisive role in the actual results of information content the reliability factors of information dissemination, users suspected degree of reliability of information significantly affects the scope of information dissemination, transmission speed, transmission threshold, propagation cycle, and the influence of dependence on network spacing is low; in addition, found that the actual influence of information dissemination for the recognition of the user of the information content of reliability, diffusion range the actual influence spread far less than information. With information content reliability factors research on social network information dissemination study, can add Deep understanding of dynamic information dissemination, enrich the theory of complex network, in order to explore the social network information dissemination and evolution provides effective help.2. derived information dissemination interference exists in the social network information dissemination process, information and the traditional interference model only from a macro point of view of information dissemination and interaction, the lack of social micro characterization network user interaction behavior. According to the interactive features of social network users and the information, analysis of the condition of producing derivative information, coexistence mode of transmission, and two yuan of user information interaction rules, and combining with multiple information model and social reinforcement theory, set up a two yuan propagation model derived information interference based on derivative interference phenomenon put forward the concept of state interference, prior and posterior state interference, constructing two yuan social enforces the rules, the success of the single user information model in one-dimensional. Extended state conversion between two-dimensional transformation relationship. Research and analysis of the derivative information interference two yuan of information dissemination based on rules and analyzed in regular networks and random networks. The experimental results show that the derivative interference case user forwarding behavior, there is obvious "phenomenon, and the interference First impressions are strongest" is mainly in the form of post in addition, checking interference; network rules for timeliness requirements are lower than the threshold of information interference random network, which shows the information dissemination rules under the network more vulnerable to interference. The derivative information derived interference and modeling, to help understand the network communication model of social network in the multi intervention phenomenon, to provide new research ideas for the study of information interference communication, it is of great theoretical value and practical significance of.3. analysis is one of the most influential individuals of individual heterogeneity in the theory of information dissemination The trade-off between efficiency and precision, has been the main problem of social network influence individual sorting algorithm. Based on social network topological features, the transfer characteristics of influence in the network structure, the center node and authoritative description of node influence, and connectivity of the central node as the core, we propose an iterative weighted the IEW index on the social network node influence (Iterative Equalization Weight). Was analyzed by Pearson correlation analysis method and the network robustness, comparing IEW index and other three kinds of classic algorithms, and in the real network data set by the information transmission dynamics model is tested. Test results show that compared to the traditional algorithm. IEW obtained a higher accuracy by sacrificing certain speed, and the reliability of the algorithm is improved. The research is put forward A new algorithm for mining is efficient, reliable, and provides a new way for node influence social network evaluation algorithm is accurate, in-depth study of social network information and influence propagation to theoretically support a role for.4. multi node communication influence maximization problem is combined with the actual analysis of information transmission theory and node influence, the traditional algorithm is based on the actual needs the flexibility to adjust the complexity of the algorithm, and the algorithm scalability is generally low. According to the law of distribution characteristics of social network node degree power, combined with the analysis of the advantages and disadvantages of the greedy algorithm and heuristic algorithm, proposed the MNH social network node influence maximization algorithm based on optimal neighbor discovery (Max Neighbor Heuristic), the algorithm to construct a set of candidate nodes by random greedy heuristic, the computing node marginal gain, approximate the maximum impact of Festival The set of points, and the efficiency and accuracy of the exchange regulation. Research using mathematical derivation and theoretical proof to verify the feasibility of the algorithm and accuracy, and in the real network data set for the Monte Carlo simulation, using independent cascade propagation model and the linear threshold propagation model, validate and compare MNH algorithm with the other three classical algorithm. The results show that: Although the MNH algorithm for solving the volatility is more obvious, but the average time in comprehensive analysis and accuracy of the algorithm has obvious advantages, and showed higher applicability. On a good combination of heuristic algorithm and greedy algorithm, in order to provide with the idea of a new method to solve the maximization problem of the social network of multi node communication influence, is an effective attempt to solve practical problems by using the theory of information transmission, has better The practical significance.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TP393.09;G206

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