本文選題：微博營銷 + 社會網(wǎng)絡(luò)分析　； 參考：《蘭州財經(jīng)大學》2015年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)絡(luò)的發(fā)展,傳統(tǒng)的營銷渠道已經(jīng)不能滿足企業(yè)的需求。新媒體營銷方式不斷涌現(xiàn),其中微博營銷最為突出。主要由于微博平臺的互動性和實時性,為企業(yè)提供了一個高效直接的營銷渠道。本文以如何找到微博內(nèi)容傳播的關(guān)鍵用戶以及該用戶所發(fā)微博的主題為切入點,以真實的微博數(shù)據(jù)為支撐,運用社會網(wǎng)絡(luò)分析方法找到微博傳播的關(guān)鍵用戶,同時運用文本挖掘的LDA模型(Latent Dirichlet Allocation,簡稱LDA),得到關(guān)鍵用戶所發(fā)微博的主題內(nèi)容�；谶@兩點分析的內(nèi)容,為企業(yè)如何成為網(wǎng)絡(luò)領(lǐng)袖以及微博營銷的主題選取提供理論支持和實際建議。本文首先介紹了研究背景和選題意義,通過國內(nèi)外學者對微博營銷、基于社會網(wǎng)絡(luò)分析的微博研究、文本挖掘的LDA模型3個方面的研究現(xiàn)狀發(fā)現(xiàn),目前并沒有將兩種方法結(jié)合使用的實際研究。然后,針對社會網(wǎng)絡(luò)的含義、特征、主要要素,以及社會網(wǎng)絡(luò)分析的相關(guān)概念和應(yīng)用,做了較詳細的研究;并且深入探討了文本預(yù)處理技術(shù)中最重要的分詞技術(shù),和文本挖掘的LDA模型的相關(guān)理論。最后,通過因特網(wǎng)抓取微博數(shù)據(jù),運用社會網(wǎng)絡(luò)分析法,確定5位轉(zhuǎn)發(fā)網(wǎng)絡(luò)以及評論網(wǎng)絡(luò)中共同存在的網(wǎng)絡(luò)領(lǐng)袖;并且運用文本挖掘的方法,挖掘網(wǎng)絡(luò)領(lǐng)袖所發(fā)微博以及評論內(nèi)容的主題,最后根據(jù)這些主題為微博營銷提出建議�；谏鐣W(wǎng)絡(luò)分析找到關(guān)鍵用戶并且挖掘該用戶所發(fā)微博內(nèi)容的主題,不僅可以有針對性的挖掘文本內(nèi)容,而且可以降低文本挖掘LDA模型的運算成本。使挖掘營銷主題的過程更為精確、高效。
[Abstract]:With the development of Internet, traditional marketing channels can not meet the needs of enterprises. New media marketing methods have been emerging, among which Weibo marketing is the most prominent. Mainly due to the interaction and real-time of Weibo platform, it provides an efficient and direct marketing channel for enterprises. Based on how to find the key users of Weibo's content dissemination and the theme of the user, and the actual data of Weibo, this paper uses the social network analysis method to find the key users. At the same time, the LDA model of text mining is used to obtain the theme content of Weibo sent by key users. Based on these two analyses, it provides theoretical support and practical advice on how to become a network leader and Weibo's marketing theme selection. This paper first introduces the research background and the significance of the topic, through the domestic and foreign scholars to Weibo marketing, social network analysis based on Weibo research, text mining LDA model of three aspects of the status quo. There is no practical study of the combination of the two methods. Then, the meaning, characteristics, main elements of social network, as well as the related concepts and applications of social network analysis, are studied in detail, and the most important word segmentation technology in text preprocessing technology is discussed in depth. And the theory of LDA model of text mining. Finally, through the Internet to grab Weibo data, using the social network analysis method, to determine the 5-bit forwarding network and comment network network co-exist network leaders, and the use of text mining method, Excavate the themes of Weibo and comments by internet leaders, and finally make suggestions for Weibo marketing based on these themes. Finding the key user and mining the subject of Weibo content based on social network analysis can not only mine text content, but also reduce the computing cost of text mining LDA model. Make the process of mining marketing themes more accurate and efficient.
【學位授予單位】：蘭州財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：F274;G206-F

【參考文獻】

相關(guān)期刊論文 前7條

1 羅永泰,王麗英,盧政營;基于隱性營銷模式的隱性廣告策略[J];當代財經(jīng);2005年04期

2 郭明;;微博網(wǎng)絡(luò)營銷對國際貿(mào)易的影響及對策[J];對外經(jīng)貿(mào);2012年12期

3 楊小朋;何躍;;騰訊微博用戶的特征分析[J];情報雜志;2012年03期

4 馮振環(huán),羅永泰;隱性營銷績效評價指標體系與方法研究[J];生產(chǎn)力研究;2004年03期

5 唐曉波;房小可;;基于文本聚類與LDA相融合的微博主題檢索模型研究[J];情報理論與實踐;2013年08期

6 周衛(wèi)國;史戎堅;葉婷;;基于Web2.0網(wǎng)站中社會網(wǎng)絡(luò)的信息挖掘[J];微計算機信息;2009年06期

7 趙文兵;朱慶華;吳克文;黃奇;;微博客用戶特性及動機分析——以和訊財經(jīng)微博為例[J];現(xiàn)代圖書情報技術(shù);2011年02期

相關(guān)碩士學位論文 前1條

1 梁賽楠;微博客受眾的媒介使用研究[D];華東師范大學;2010年

，

本文編號：1786758