【摘要】：互聯(lián)網的迅速發(fā)展和廣泛應用,使得網絡輿情隨之成為社會輿情最主要組成部分,微博所具備的社交網絡特性和媒體傳播特性使其成為了最具影響力的網絡輿情衍生場所之一�，F(xiàn)有研究多是根據網絡輿情演化結果進行研究,一直處于被動的問題解決狀態(tài),無法充分滿足對網絡輿情的事前預警和事中實時發(fā)現(xiàn)需求。網絡輿情潛在主題發(fā)現(xiàn)能夠及時探測出網絡輿情的核心內容,有助于正確把握網絡輿情的產生規(guī)律和演化機制,對于構建良好的網絡輿情環(huán)境具有重要意義。研究首先對已有網絡輿情主題發(fā)現(xiàn)研究成果進行梳理分析,基于已有的少量潛在主題發(fā)現(xiàn)研究成果結合本研究目標對網絡輿情潛在主題進行了定義;其次,對社會網絡分析方法理論進行概述,著重對研究用到的社區(qū)發(fā)現(xiàn)方法和節(jié)點中心性方法原理進行說明分析;再次,對微博數(shù)據進行分析,包括微博內容,微博用戶屬性和行為數(shù)據,并梳理了與微博影響力相關研究理論方法,分析其與用戶行為的關系。在此基礎之上,研究構建網絡輿情潛在主題發(fā)現(xiàn)模型,并對模型中用到的關鍵指標和方法進行說明:(1)基于微博用戶行為構建用戶行為關系網絡,對不同用戶行為和關注關系賦予特定權重;(2)利用社區(qū)發(fā)現(xiàn)方法對用戶關系網絡進行社區(qū)發(fā)現(xiàn),并計算網絡節(jié)點相關中心性指標;(3)計算重要社區(qū)中用戶節(jié)點影響力并降序排列,篩選關鍵用戶節(jié)點;(4)將社區(qū)關鍵用戶節(jié)點映射到對應微博,獲得關鍵微博節(jié)點;(5)通過TF-IDF方法對關鍵微博節(jié)點內容關鍵詞排序,篩選出備選潛在主題詞進行共詞分析,獲得潛在主題詞集列表進行主題解讀。最后,以"魏則西事件"作為研究案例,對模型效果進行實例驗證,證實了本研究網絡輿情潛在主題發(fā)現(xiàn)模型的有效性。
[Abstract]:With the rapid development and wide application of the Internet, network public opinion has become the most important part of social public opinion, and Weibo has become one of the most influential derivative places of network public opinion because of its social network characteristics and media dissemination characteristics. Most of the existing studies are based on the results of the evolution of network public opinion, which has been in a passive state of solving the problem, and can not fully meet the need of pre-warning and real-time discovery of network public opinion. The discovery of the potential topic of network public opinion can detect the core content of network public opinion in time, help to correctly grasp the law and evolution mechanism of network public opinion, and have important significance for the construction of good network public opinion environment. The research firstly combs and analyzes the existing research results on the topic discovery of network public opinion, and defines the potential topic of network public opinion based on a small number of existing research results combined with the objectives of this research; secondly, The social network analysis method theory is summarized, especially the community discovery method and node-centered method used in the research are explained and analyzed. Thirdly, the Weibo data, including Weibo content, are analyzed. Weibo user attributes and behavior data, and combing the theory and methods related to Weibo influence, and analyzing the relationship between Weibo and user behavior. On this basis, the potential topic discovery model of network public opinion is constructed, and the key indicators and methods used in the model are explained: (1) constructing user behavior relationship network based on Weibo user behavior; Give specific weight to different user behavior and relationship of concern; (2) use community discovery method to discover user relationship network and calculate relevant central index of network node; (3) calculate the influence and descending order of user node in important community. Screening key user nodes; (4) mapping community key user nodes to corresponding Weibo to obtain key Weibo nodes; (5) sorting key Weibo node content keywords by TF-IDF method, and selecting alternative potential theme words for coterm analysis. Get a list of potential theme words for topic interpretation. Finally, taking Wei Zexi incident as a case study, the effectiveness of the model is verified by an example, which verifies the validity of the model.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：C912.3;C913.4

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