本文關鍵詞： 微博 數(shù)據(jù)獲取 話題檢測 時間相似度 用戶權威度　出處：《昆明理工大學》2014年碩士論文　論文類型：學位論文

【摘要】：隨著互聯(lián)網(wǎng)技術的迅猛發(fā)展,網(wǎng)絡媒體已經(jīng)成為人們日常生活中不可或缺的一種傳播媒介。其中,微博作為新興典型代表之一,以極快的速度影響著社會傳播格局。用戶可以通過微博隨時隨地的更新個人狀態(tài)和參與討論自己喜愛或關心的話題,使得微博成為社會熱點話題產(chǎn)生的聚集地。對微博進行話題檢測,不僅能向用戶提供熱點話題信息,還能為政府部門進行突發(fā)事件監(jiān)測、輿情分析等方面提供強有力的數(shù)據(jù)支持,因此研究如何從海量的微博信息中檢測出熱門話題具有十分重要的現(xiàn)實意義。 微博文本相對于傳統(tǒng)文本來說差異較大,除了大量的省略、指代及主觀性的個性化語言之外,還有文本較短,話題離散性、實時性和互動性等特點。因而,傳統(tǒng)的文本話題檢測方法不能直接應用于微博,故本文在研究過程中結合微博自身的特性,提出了一種基于用戶權威度的中文微博話題檢測方法。 首先,在本文的話題檢測算法中引入用戶威權度,把用戶的粉絲數(shù)量作為微博影響力的重要參考因素,與以往只針對無結構文本分析的話題檢測算法相比,提高了話題檢測的準確度；其次,一般的話題檢測方法不重視時間因素,而本文把時間因素作為檢測話題的重要參數(shù),把微博時間限制在一個有效期內,使得話題發(fā)現(xiàn)的更加精確；最后,傳統(tǒng)方法中話題檢測與話題排序是相互獨立的,不能直接利用檢測的結果對話題排序,而本文在對話題進行檢測過程中,引入了基礎能量和相關性能量的概念并以此作為話題能量,在話題檢測完成后可以依據(jù)話題能量大小對話題直接進行排序。
[Abstract]:With the rapid development of Internet technology, Internet media has become an indispensable media in people's daily life. At an extremely fast speed, it affects the social communication pattern. Users can update their personal status and participate in discussions on topics they like or care about through Weibo at any time and anywhere. Weibo has become a gathering place for hot social topics. The topic detection of Weibo can not only provide users with information on hot topics, but also monitor emergencies for government departments. The analysis of public opinion provides strong data support, so it is of great practical significance to study how to detect hot topics from mass Weibo information. Weibo's text is quite different from the traditional text. In addition to a large number of individualized languages such as ellipsis, reference and subjectivity, there are also features such as shorter text, discrete topic, real-time and interactive, etc. The traditional text topic detection method can not be directly applied to Weibo, so this paper puts forward a new topic detection method based on user authority, which is based on the characteristics of Weibo itself. First of all, the user authority is introduced into the topic detection algorithm in this paper, and the number of users' fans is regarded as an important reference factor of Weibo's influence, compared with the previous topic detection algorithm, which only focuses on unstructured text analysis. The accuracy of topic detection is improved. Secondly, the general method of topic detection does not attach importance to time factor, and this paper regards time factor as an important parameter of detecting topic, and limits Weibo's time to a period of validity. Finally, the traditional methods of topic detection and topic ranking are independent of each other, can not directly use the results of the detection of topics ranking, and this paper in the process of topic detection, The concepts of basic energy and correlation energy are introduced and used as topic energy. After topic detection is completed, topics can be sorted directly according to the magnitude of topic energy.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.092

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