【摘要】：隨著大眾媒體的發(fā)展與普及,互聯(lián)網(wǎng)已經(jīng)成為網(wǎng)絡(luò)用戶獲取信息、表達(dá)意見、交流看法的重要平臺(tái)。官方新聞網(wǎng)站發(fā)布的信息經(jīng)過民間社交網(wǎng)絡(luò)的討論形成輿論流,影響事件的傳播與演化過程。然而信息在以權(quán)威媒體為代表的官方輿論場與以個(gè)體網(wǎng)絡(luò)用戶為代表的民間輿論場的交互機(jī)制尚不明確,進(jìn)而當(dāng)突發(fā)事件爆發(fā)時(shí)難以控制不良情感的發(fā)生、傳播與演化。因此,事件的網(wǎng)絡(luò)輿情發(fā)展肌理已經(jīng)引起了大量研究者的興趣。用戶在網(wǎng)絡(luò)中的行為是其在現(xiàn)實(shí)世界中行為的映射,用戶的內(nèi)在特征影響事件的信息的傳播與演化過程,反應(yīng)在網(wǎng)絡(luò)中即為發(fā)表言論及其所表達(dá)心情的差異。因此,通過挖掘用戶在網(wǎng)絡(luò)中的言論行為以及用戶的情感態(tài)度能夠發(fā)現(xiàn)用戶的個(gè)性化屬性,進(jìn)而能夠分析其在事件傳播與演化中的角色與作用。在社交網(wǎng)絡(luò)中,信息經(jīng)過轉(zhuǎn)發(fā)、評論、點(diǎn)贊等方式進(jìn)行傳播,同時(shí)若用戶在轉(zhuǎn)發(fā)與評論信息時(shí)添加個(gè)人看法,那么便促進(jìn)了事件的演化。鑒于此,本文結(jié)合認(rèn)知科學(xué)與媒體傳播學(xué)科的研究方法和手段,對網(wǎng)絡(luò)中用戶的基本屬性、性格屬性,以及信息傳播機(jī)制、事件情感走勢等問題進(jìn)行了研究。重點(diǎn)討論了影響網(wǎng)絡(luò)輿情傳播與演化過程的用戶模型與事件傳播演化模型,并對用戶的背景情感知識(shí)進(jìn)行計(jì)算表達(dá),從微觀與宏觀兩個(gè)方面對用戶的信息接受與傳播機(jī)制進(jìn)行研究。論文的主要工作和創(chuàng)新點(diǎn)如下:1.基于社會(huì)心理學(xué)對情感分析的結(jié)論,提出基于模糊邏輯的多維多粒度情感計(jì)算方法。該方法依賴具體語境,計(jì)算詞匯在語境中的情感,同時(shí)自適應(yīng)加入網(wǎng)絡(luò)流行用語。此外,基于模糊邏輯的方法使得詞匯或者微博在各個(gè)維的隸屬度均為[0,1],打破其加和為1的限制,這一點(diǎn)使得情感的模糊計(jì)算更加符合人類的認(rèn)知過程。2.基于社交網(wǎng)絡(luò)相關(guān)數(shù)據(jù),建立用戶模型。該用戶模型考慮用戶的基本屬性,包括用戶的性別、年齡、教育水平,并對缺失基本屬性的用戶信息進(jìn)行補(bǔ)全。此外該用戶模型包括用戶內(nèi)容背景知識(shí)、用戶興趣點(diǎn)、情感背景知識(shí)、個(gè)性化性格特征等,挖掘用戶在接收信息與傳播信息的個(gè)性化特征。3.提出基于官方輿論場與民間輿論場的事件情感交互分析方法。該方法不僅對事件的內(nèi)容分析,而且對事件的情感進(jìn)行度量,并進(jìn)一步提取官方輿論場與民間輿論場的誘導(dǎo)關(guān)系。該方法能夠輔助預(yù)測事件發(fā)展趨勢,進(jìn)而可以為調(diào)控事件提出決策建議。4.基于網(wǎng)絡(luò)動(dòng)力學(xué),研究用戶在信息傳播時(shí)的級聯(lián)現(xiàn)象。在用戶聯(lián)系緊密的社區(qū)內(nèi)部,容易形成信息傳播的級聯(lián)現(xiàn)象;在社區(qū)之間,用戶之間聯(lián)系疏松時(shí),容易形成信息演化現(xiàn)象。一旦形成級聯(lián),事件的原始信息便發(fā)生丟失,出現(xiàn)“隨大流”現(xiàn)象。
[Abstract]:With the development and popularization of mass media, the Internet has become an important platform for network users to obtain information, express opinions and exchange views. The information released by the official news website is discussed by the folk social network to form the public opinion flow, which affects the process of the event's propagation and evolution. However, the interaction mechanism of information between the official public opinion field represented by the authoritative media and the folk public opinion field represented by individual network users is not clear, and it is difficult to control the occurrence, dissemination and evolution of bad emotions when emergencies break out. Therefore, the development of network public opinion has attracted the interest of a large number of researchers. The behavior of users in the network is the mapping of their behavior in the real world. The inherent characteristics of users affect the process of information dissemination and evolution of events. Therefore, by mining the user's speech behavior in the network and the user's emotional attitude, we can discover the personalized attributes of the user, and then analyze its role and role in the event propagation and evolution. In social networks, the information is transmitted by forwarding, commenting and liking, and if users add their own opinions when forwarding and commenting on the information, it will promote the evolution of events. In view of this, combined with the research methods and means of cognitive science and media communication, this paper studies the basic attributes, personality attributes, information communication mechanism and event emotion trend of users in the network. The user model and event propagation evolution model, which affect the process of network public opinion propagation and evolution, are discussed, and the background emotional knowledge of users is calculated and expressed. This paper studies the mechanism of information acceptance and dissemination from micro and macro aspects. The main work and innovation are as follows: 1. Based on the conclusion of affective analysis in social psychology, a multi-dimensional and multi-granularity emotional calculation method based on fuzzy logic is proposed. The method relies on specific context, calculates the emotion of vocabulary in context, and adaptively adds popular online terms. In addition, the fuzzy logic based approach makes the membership of vocabulary or Weibo in each dimension [0 / 1], breaking the limit of the sum of 1, which makes the fuzzy calculation of emotion more in line with the cognitive process of human beings. 2. Based on the relevant data of social network, the user model is established. The user model considers the basic attributes of the user, including the user's gender, age and education level, and complements the user information that lacks the basic attribute. In addition, the user model includes user content background knowledge, user interest point, emotional background knowledge, personalized personality features, etc. A method of event emotion interaction analysis based on official public opinion field and folk public opinion field is proposed. This method not only analyzes the content of the event, but also measures the emotion of the event, and further extracts the inductive relationship between the official public opinion field and the public opinion field. This method can help to predict the trend of event development, and then can make decision suggestions for the control of events. 4. 4. Based on network dynamics, the concatenation phenomenon of users in the process of information transmission is studied. It is easy to form cascading phenomenon of information dissemination in the community where users are closely connected, and the phenomenon of information evolution is easy to form when the connection between communities is loose. Once the cascade is formed, the original information of the event is lost and the phenomenon of "following the stream" occurs.
【學(xué)位授予單位】：上海大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP393.09

【共引文獻(xiàn)】

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本文編號(hào)：2409753