發(fā)布時(shí)間：2018-07-05 08:21

  本文選題：微博 + 用戶可信度　； 參考：《蘭州交通大學(xué)》2015年碩士論文

【摘要】：微博作為一種新型的社交網(wǎng)絡(luò)平臺(tái)正受到越來(lái)越多人的青睞,使用微博平臺(tái)分享和獲取信息已經(jīng)成為人們交流的重要方式。由于微博的自發(fā)性、低約束等特點(diǎn),以及缺乏對(duì)用戶有效的管理與制約手段,導(dǎo)致在微博用戶數(shù)量快速增長(zhǎng)與微博信息飛速傳播過(guò)程中,微博虛假信息及謠言泛濫。因此,微博用戶可信度問(wèn)題逐漸引起人們的關(guān)注,成為一個(gè)亟待解決的問(wèn)題。微博信息屬于互聯(lián)網(wǎng)信息的一部分,其短文本格式和復(fù)雜的社交網(wǎng)絡(luò)特性給微博用戶及其信息的可信度研究帶來(lái)了巨大挑戰(zhàn)。目前,微博用戶可信度研究方面取得了一些初步成果,但存在著評(píng)價(jià)方法單一,元素特征考慮簡(jiǎn)單,算法復(fù)雜度高等不足。本文基于現(xiàn)有微博可信度研究成果,以新浪微博為研究對(duì)象,運(yùn)用社會(huì)網(wǎng)絡(luò)平衡理論知識(shí)對(duì)微博用戶間信任傳遞關(guān)系進(jìn)行分析。并從鏈接分析角度出發(fā),基于PageRank算法思想,結(jié)合用戶的特征屬性,研究了一種評(píng)估微博用戶可信度的模型及算法,針對(duì)同一微博領(lǐng)域用戶的可信度排序進(jìn)行相應(yīng)的實(shí)驗(yàn)及分析。論文主要研究?jī)?nèi)容如下:首先,論文分析了微博的結(jié)構(gòu)特點(diǎn),研究了新的交流模式對(duì)用戶可信度行為造成的影響,綜述了可信度研究相關(guān)理論與主要技術(shù),探討了微博信息可信度研究?jī)?nèi)容,對(duì)比分析了當(dāng)前微博可信度研究模型和表示方法。其次,論文基于微博信息傳播機(jī)制及社會(huì)網(wǎng)絡(luò)平衡理論,分析微博用戶之間的信任傳遞關(guān)系,發(fā)現(xiàn)穩(wěn)定微博網(wǎng)絡(luò)結(jié)構(gòu)中可信度相近用戶之間更易建立關(guān)聯(lián)�；赑ageRank思想,將微博用戶可信度排序問(wèn)題轉(zhuǎn)化為群體用戶的信任支持問(wèn)題,而用戶間的鏈接即是用戶因需求而產(chǎn)生的信任支持行為,進(jìn)而從鏈接分析角度提出了微博用戶可信度評(píng)估模型。最后,論文分析微博用戶的特征屬性及相關(guān)行為關(guān)系,結(jié)合本文模型設(shè)計(jì)了相應(yīng)的可信度排序算法。算法利用非平均權(quán)值的思想,更加強(qiáng)調(diào)用戶粉絲質(zhì)量的重要性,能夠有效降低用戶可信度得分排序結(jié)果中僵尸粉的影響�；诰W(wǎng)絡(luò)爬蟲(chóng)獲得的微博群體用戶數(shù)據(jù)的實(shí)驗(yàn)結(jié)果表明了算法的有效性。
[Abstract]:As a new type of social network platform, Weibo is being favored by more and more people. Using Weibo platform to share and obtain information has become an important way for people to communicate. Due to the characteristics of Weibo, such as spontaneity, low constraint and lack of effective management and restriction measures to users, Weibo false information and rumors are rampant in the process of rapid growth of Weibo users and rapid spread of Weibo information. Therefore, the issue of Weibo user credibility has gradually attracted people's attention and become a problem to be solved. Weibo information is a part of Internet information. Its short text format and complex social network feature bring great challenges to the credibility of Weibo users and their information. At present, some preliminary achievements have been made in the research of Weibo user reliability, but there is a single evaluation method, simple consideration of element features and high complexity of the algorithm. Based on the existing research results of Weibo credibility and taking Sina Weibo as the research object, this paper analyzes the trust transfer relationship between Weibo users using the theory of social network balance. From the point of view of link analysis, based on the idea of PageRank algorithm and the characteristic attributes of users, this paper studies a model and algorithm to evaluate the reliability of Weibo users, and carries out corresponding experiments and analyses for the ranking of users' credibility in the same Weibo domain. The main contents of this paper are as follows: firstly, this paper analyzes the structural characteristics of Weibo, studies the influence of new communication mode on user's credibility behavior, and summarizes the relevant theories and main technologies of credibility research. This paper discusses the research content of Weibo information credibility, and compares and analyzes the current research model and representation method of Weibo credibility. Secondly, based on Weibo information transmission mechanism and social network balance theory, this paper analyzes the trust transfer relationship between Weibo users, and finds that it is easier to establish the correlation between users with similar credibility in stabilizing Weibo network structure. Based on the idea of PageRank, the problem of Weibo user credibility ranking is transformed into the trust support problem of group users, and the link between users is the trust support behavior caused by users' requirements. Then, from the point of view of link analysis, the Weibo user reliability evaluation model is proposed. Finally, this paper analyzes the characteristic attributes and related behaviors of Weibo users, and designs the corresponding reliability ranking algorithm combined with this model. By using the idea of non-average weights, the algorithm emphasizes the importance of the quality of users' fans and can effectively reduce the influence of zombie powder in the ranking results of users' credibility scores. The experimental results of Weibo user data based on crawler show the effectiveness of the algorithm.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP393.092

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

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本文編號(hào)：2099586