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  本文關鍵詞：復雜社交網絡中基于Agent模型的個體觀點預測　出處：《東南大學》2017年碩士論文　論文類型：學位論文

  更多相關文章： 個體觀點預測 復雜社交網絡 復雜自適應理論 Agent個體模型 Multi-Agent觀點交互模型

【摘要】：近年來,隨著移動終端產品的普及和社交平臺的不斷發(fā)展,人們越來越習慣使用社交網絡平臺進行人與人之間的溝通交流。然而,社交平臺的匿名化慢慢滋生了一群鍵盤俠,同時,用戶的從眾心理及法不責眾的心態(tài)也使網絡極端事件頻有發(fā)生,且由于社交平臺中的信息擴散速度之快,政府等相關部門不易做好防范措施。針對上述問題,就復雜社交網絡中的個體對某一話題的觀點進行預測,對維護網絡社會的和諧和安全是充分且必要的。眾所周知,不同的個體對同一話題會持有不同的觀點,且個體對他人觀點的認可程度會略有差異,受他人觀點的影響程度也會不盡相同。因此,為較好反映個體在形成自我觀點時考慮的各類影響因素,本文綜合考慮復雜自適應系統(tǒng)中的Agent概念,提出并設計Agent個體模型和Multi-Agent觀點交互模型,從微觀角度分析社交網絡中某一話題社區(qū)觀點演變過程,并能預測個體對該話題產生的觀點傾向。為達到較好的預測效果,本文首先從抓取的實證數(shù)據(jù)中挖掘出若干話題社區(qū),建立Multi-Agent話題社區(qū)環(huán)境,并在此基礎上對社區(qū)中所有博文及評論文本信息隱含的情感傾向進行挖掘。建立話題社區(qū)網絡動態(tài)模型,模擬社交網絡節(jié)點間的關注關系及交互關系。其次,建立基于Agent的個體模型,設計Agent結構,將個體接收信息產生觀點的過程映射為Agent通過感知器、控制器、效應器處理消息生成觀點的過程,使話題社區(qū)中的Agent具有自主性、適應性、社交性、交互性四大特點。并將個體自信度、鄰居依賴度、社區(qū)趨同度三個特征作為Agent個體形成觀點過程中的影響因素。隨后,建立Multi-Agent觀點交互模型,實現(xiàn)話題社區(qū)環(huán)境中Agent間通訊、交互。并設計Agent個體觀點交互規(guī)則生成算法,學習特征權值向量。本文在新浪微博實證數(shù)據(jù)上對Agent個體模型和Multi-Agent觀點交互模型的有效性進行了驗證。實驗結果表明:(a)從微觀個體角度分析,基于Agent的個體模型和基于Multi-Agent觀點交互模型能夠較準確的預測個體觀點變化的轉折點,對話題社區(qū)活躍個體的預測結果與實際結果出入甚微。(b)從宏觀話題社區(qū)角度分析,利用基于Agent的個體模型和基于Multi-Agent觀點交互模型能夠較好預測話題社區(qū)所有個體的觀點變化趨勢,且可預測極端群體的規(guī)模。
[Abstract]:In recent years, with the popularity of mobile terminal products and the continuous development of social platform, people are more and more used to use social network platform to communicate between people. The anonymity of social platform has slowly bred a group of keyboard knights, at the same time, the mentality of users' conformity and blame also makes the network extreme events occur frequently, and because of the rapid spread of information in the social platform. The government and other relevant departments are not easy to take precautions. In response to the above problems, the individuals in the complex social networks on a certain topic point of view are predicted. It is necessary and sufficient to maintain the harmony and security of the network society. As we all know, different individuals will hold different views on the same topic, and the degree of recognition of the views of others will be slightly different. Therefore, in order to better reflect the various factors that individuals consider in the formation of self-view, this paper comprehensively considers the concept of Agent in complex adaptive systems. This paper proposes and designs the Agent individual model and the Multi-Agent viewpoint interactive model, and analyzes the evolution process of a topic community viewpoint in social network from the micro point of view. And can predict the individual opinion tendency on this topic. In order to achieve better prediction effect, this paper first excavates a number of topic communities from the collected empirical data. The Multi-Agent topic community environment is established, and on this basis, the emotional tendency of all blog posts and comments text information in the community is excavated, and the dynamic model of topic community network is established. Simulation of social network nodes between the relationship of concern and interaction. Secondly, establish an individual model based on Agent, design the structure of Agent. The process of individual receiving information to produce ideas is mapped to the process of Agent processing message generation ideas through perceptron controller and effector so that Agent in the topic community has autonomy and adaptability. Social, interactive four characteristics. And the individual confidence degree, neighborhood dependence, community convergence degree of three characteristics as the Agent individual formation of the process of influence factors. Establish Multi-Agent viewpoint interaction model, realize communication and interaction between Agent in topic community environment, and design Agent individual viewpoint interaction rule generation algorithm. The effectiveness of the Agent individual model and the Multi-Agent viewpoint interaction model is verified based on the Sina Weibo empirical data. The experimental results show that the Agent individual model and the Multi-Agent viewpoint interaction model are effective. From a microscopic perspective. The individual model based on Agent and the interactive model based on Multi-Agent viewpoint can accurately predict the turning point of individual viewpoint change. The prediction results of active individuals in the topic community are only slightly different from the actual results. (B) from the perspective of macro-topic community analysis. The individual model based on Agent and the interactive model based on Multi-Agent viewpoint can predict the trend of change of opinion of all individuals in the topic community, and can predict the scale of extreme group.
【學位授予單位】：東南大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP393.09

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