發(fā)布時(shí)間：2018-05-23 22:47

  本文選題：網(wǎng)絡(luò)輿情 + 元胞自動(dòng)機(jī)�。� 參考：《河南科技大學(xué)》2017年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)的飛速發(fā)展,網(wǎng)絡(luò)輿情廣受社會關(guān)注。網(wǎng)絡(luò)輿情研究內(nèi)容涵蓋社會科學(xué)和自然科學(xué),是當(dāng)前的研究熱點(diǎn)。研究網(wǎng)絡(luò)信息傳播規(guī)律,有助于理解信息傳播機(jī)制,分析影響信息傳播的因素,了解網(wǎng)絡(luò)用戶拓?fù)涮卣?揭示復(fù)雜現(xiàn)象背后的本質(zhì)規(guī)律,進(jìn)而為網(wǎng)絡(luò)話題發(fā)展趨勢預(yù)測的研究和應(yīng)用提供理論指導(dǎo)。本文以真實(shí)網(wǎng)絡(luò)信息交互現(xiàn)象為出發(fā)點(diǎn),結(jié)合交叉學(xué)科領(lǐng)域的研究和建模方法,分析網(wǎng)絡(luò)用戶行為特征,針對觀點(diǎn)交流和傳播過程建模,研究群體觀點(diǎn)聚合、分化、演進(jìn),并探討了網(wǎng)絡(luò)輿論的導(dǎo)控策略。本文主要工作包括:1.在傳統(tǒng)元胞自動(dòng)機(jī)模型的基礎(chǔ)上結(jié)合Bass理論加入外部影響力,并引入鄰域影響度和外部影響度兩個(gè)變量,建立考慮外部影響的元胞自動(dòng)機(jī)網(wǎng)絡(luò)輿情傳播模型。提出了改進(jìn)的傾向性轉(zhuǎn)換計(jì)算公式,并使用粗、細(xì)粒度統(tǒng)計(jì)方法對模型進(jìn)行了仿真分析。新模型揭示了網(wǎng)絡(luò)輿情傳播的一些規(guī)律,有助于網(wǎng)絡(luò)輿情管理者分析、預(yù)測、管理和控制輿情傳播趨勢。2.研究輿論主體的主觀能動(dòng)性對觀點(diǎn)演化的影響,改進(jìn)經(jīng)典有限信任模型,引入了堅(jiān)定度、信任度和記憶長度的概念,提出新的度量個(gè)體間交互影響力的方法,建立基于加速增長HK網(wǎng)絡(luò)的含有記憶機(jī)制的網(wǎng)絡(luò)輿情演化模型。新模型綜合考慮用戶間影響力、信任閾值和個(gè)體記憶策略對信任關(guān)系的影響,更加符合實(shí)際網(wǎng)絡(luò)環(huán)境中群體觀點(diǎn)交流的特點(diǎn)。
[Abstract]:With the rapid development of the Internet, network public opinion is widely concerned by the society. The research content of network public opinion covers social science and natural science, and it is a hot research topic at present. Studying the law of network information dissemination is helpful to understand the mechanism of information dissemination, analyze the factors that influence information dissemination, understand the topological characteristics of network users, and reveal the essential laws behind complex phenomena. Then it provides theoretical guidance for the research and application of network topic trend prediction. Based on the phenomenon of real network information interaction, this paper analyzes the behavior characteristics of network users by combining the cross-disciplinary research and modeling methods, models the process of view exchange and dissemination, studies the aggregation, differentiation and evolution of group views. And discusses the network public opinion guidance and control strategy. The main work of this paper includes: 1. Based on the traditional cellular automata model, the external influence is added to the Bass theory, and two variables, the neighborhood influence degree and the external influence degree, are introduced to establish the cellular automata network public opinion propagation model considering the external influence. An improved formula for calculating tendency conversion is proposed, and the model is simulated and analyzed by using coarse and fine grained statistical methods. The new model reveals some laws of the spread of network public opinion and helps network public opinion managers to analyze, predict, manage and control the trend of public opinion communication. This paper studies the influence of subjective initiative of public opinion on the evolution of opinions, improves the classical finite trust model, introduces the concepts of firmness, trust and memory length, and puts forward a new method to measure the interaction influence between individuals. A network public opinion evolution model with memory mechanism based on accelerating growth HK network is established. The new model considers the influence of user influence, trust threshold and individual memory strategy on trust relationship, which is more consistent with the characteristics of group view exchange in real network environment.
【學(xué)位授予單位】：河南科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：O157.5

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