【摘要】：近年來(lái)隨著互聯(lián)網(wǎng)的普及和深入，越來(lái)越多的網(wǎng)絡(luò)水軍活躍在各大社會(huì)媒體上，包括論壇、微博、博客、淘寶等。從事話題炒作，事件營(yíng)銷等危害性行為，干擾輿情的正常傳播，誤導(dǎo)輿論方向，，危害輿情安全，有必要對(duì)其行為特征進(jìn)行研究。文中采用基于功能語(yǔ)義的信息抽取技術(shù)和相關(guān)算法采集了國(guó)內(nèi)五大論壇上某個(gè)版塊一段時(shí)間的發(fā)布數(shù)據(jù)；并從中提取了帳戶、貼文和評(píng)論的基本屬性；在對(duì)網(wǎng)絡(luò)帳戶進(jìn)行人工分類的基礎(chǔ)上，分析了水軍貼文和評(píng)論的分布情況；驗(yàn)證了水軍及其行為嚴(yán)重影響論壇輿論的結(jié)論。貼文和評(píng)論是水軍行為的結(jié)果，本文以貼文的發(fā)表時(shí)間和評(píng)論的回復(fù)時(shí)間為研究對(duì)象，通過(guò)分析不同周期內(nèi)和不同時(shí)間起點(diǎn)的貼文和評(píng)論的統(tǒng)計(jì)數(shù)量分布，來(lái)尋找水軍的群體性行為特征，得到了小時(shí)周期上的典型三峰分布，提供了水軍群體協(xié)同性的有效證據(jù)，從行為特征上驗(yàn)證網(wǎng)絡(luò)水軍是一個(gè)有組織的彼此協(xié)同的行為群體。 此外本文還利用社區(qū)發(fā)現(xiàn)算法，在范純龍等人提出的基于賬戶同帖率關(guān)系網(wǎng)構(gòu)建的基礎(chǔ)上進(jìn)行水軍社區(qū)結(jié)構(gòu)分析和水軍組織發(fā)現(xiàn)，然后利用Pajak軟件構(gòu)建網(wǎng)絡(luò)水軍的社區(qū)結(jié)構(gòu)圖，從而以可視化的形式再現(xiàn)網(wǎng)絡(luò)水軍的組織模式。再次從社區(qū)結(jié)構(gòu)和組織發(fā)現(xiàn)上為水軍行為活動(dòng)具有協(xié)同性和組織性提供了有效證據(jù)，從組織結(jié)構(gòu)上驗(yàn)證網(wǎng)絡(luò)水軍是一個(gè)有組織有結(jié)構(gòu)的，具有高度協(xié)同性的網(wǎng)絡(luò)組織。
[Abstract]:In recent years, with the popularization and deepening of the Internet, more and more network water forces are active in the major social media, including forums, micro-blog, blogs, Taobao and so on. It is necessary to conduct research on their behavior characteristics by disturbing the normal dissemination of public opinion, misleading public opinion and endangering public opinion. The information extraction technology based on functional semantics and related algorithms are used to collect data of a period of time on a block on the five major forums in China; and the basic attributes of accounts, posts and comments are extracted from it. On the basis of artificial classification of network accounts, the distribution of Water Army posts and comments is analyzed. The water army and its behavior seriously affect the conclusion of the forum public opinion. The paper and comments are the result of the water army's behavior. This paper takes the time of publication and the reply time of the comments as the research object. By analyzing the statistical quantity distribution of the posts and comments in different cycles and different time starting points, the paper finds the characteristics of the group behavior of the water army. The typical three peak distribution on the hour period provides the effective evidence of the association of the water army groups, and verifies that the network water army is an organized and cooperative behavior group from the behavioral characteristics.
In addition, this paper also uses the community discovery algorithm, on the basis of Fan Chunlong et al. Based on the construction of the relationship network based on the account with the relationship network construction, water army community structure analysis and water army organization discovery, and then use Pajak software to construct the network water Army Community Structure Map, thus reproducing the network water army organization pattern in the form of visualization. The discovery of community structure and organization provides effective evidence for the synergism and organization of the water army's behavior. From the organizational structure, it is proved that the network water army is a structured and highly cooperative network organization.
【學(xué)位授予單位】：沈陽(yáng)航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.08

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