【摘要】：微博作為一種新興的社交媒體被廣泛使用,其每天的數(shù)據(jù)交流數(shù)量呈現(xiàn)爆炸式的增長,這些數(shù)據(jù)為自然語言處理提供了良好的語料環(huán)境。微博文本具有和短文本一樣的長度較短、情感表達(dá)強(qiáng)烈、話題單一的特點(diǎn),這就需要通過不同于長文本情感分析的方法來處理。本文通過對短文本情感分析進(jìn)行改進(jìn),將上下文的觀點(diǎn)信息加入到情感計算中,同時建立微博表情符號情感詞典,最終得到情感傾向性結(jié)果。本文首先對微博評論文本的處理技術(shù)進(jìn)行研究和探討,然后融合微博表情符號情感詞典自動構(gòu)建方法構(gòu)建微博情感詞典,同時抽取出微博評論的上下文觀點(diǎn)信息,最后對這些信息進(jìn)行整合處理,得到情感傾向性分析結(jié)果。本文所做的工作主要包含以下三個方面的內(nèi)容:(1)提出了基于微博表情符號的情感詞典自動構(gòu)建方法,并應(yīng)用于微博評論情感分析微博評論文本通常具有主觀情感,并且領(lǐng)域廣泛,因此在進(jìn)行情感傾向性分析之前我們要正確分析出微博評論的情感信息。情感詞典的完善程度決定了情感分析準(zhǔn)確率的高低,在考慮微博表情符號對微博文本情感傾向的影響以及情感詞典構(gòu)建的基礎(chǔ)上,提出一種融合表情符號的情感詞典自動構(gòu)建方法。該方法首先利用COAE2015任務(wù)一中提供的訓(xùn)練數(shù)據(jù)集對其進(jìn)行分詞、去重等操作,然后獲得情感詞并得到其在正負(fù)向語料中的出現(xiàn)次數(shù),最后再利用PMI計算其情感傾向性大小,最終生成情感詞典。(2)研究上下文觀點(diǎn)信息對情感傾向性的影響,提出一種基于上下文觀點(diǎn)信息的情感傾向分析方法在進(jìn)行情感傾向性分析之前,首先要對文本當(dāng)中的上下文觀點(diǎn)進(jìn)行界定。由于用戶在發(fā)表評論時或多或少的會受到原始文本以及其前面評論的影響,本文提出了基于上下文觀點(diǎn)信息的情感傾向性分析方法,并將其應(yīng)用到微博評論中的情感分析當(dāng)中。該方法首先對評論文本按照評論的先后次序進(jìn)行編號,按照次序的大小對評論文本進(jìn)行賦值權(quán)重,最后結(jié)合建立的情感詞典,獲得算法最終的情感傾向。(3)設(shè)計并實(shí)現(xiàn)了基于上下文觀點(diǎn)信息的微博情感傾向性分析原型系統(tǒng)在分析微博評論文本的情感傾向性過程中,針對每個方面設(shè)計了相對應(yīng)的功能模塊,并實(shí)現(xiàn)了基于上下文觀點(diǎn)信息的微博情感傾向性分析原型系統(tǒng)。該系統(tǒng)可以對微博當(dāng)中出現(xiàn)的評論文本進(jìn)行挖掘抽取、分析處理,并最終向用戶提供直觀的情感傾向性。
[Abstract]:As a new kind of social media, Weibo is widely used, and its daily data exchange is increasing explosively. These data provide a good corpus environment for natural language processing. Weibo texts have the characteristics of short length, strong emotional expression and single topic, which need to be dealt with differently from the long text emotional analysis method. In this paper, we improve the emotional analysis of the short essay, add the viewpoint information of the context to the emotional calculation, and establish the emotional dictionary of the Weibo emoticons, and finally get the emotional preference results. In this paper, the processing technology of Weibo comment text is studied and discussed, then the Weibo emotional dictionary is constructed by using the Weibo emoticons emotional dictionary, and the context view information of Weibo comments is extracted at the same time. Finally, the integration of these information is processed, and the emotional orientation analysis results are obtained. The work of this paper mainly includes the following three aspects: (1) the automatic construction method of emotion dictionary based on Weibo emoticons is proposed, and it is applied to the analysis of Weibo comments in Weibo comments. And it has a wide range of fields, so we should correctly analyze the emotional information of Weibo comments before we do emotional orientation analysis. The perfect degree of emotion dictionary determines the accuracy of emotion analysis. On the basis of considering the influence of Weibo emoji on the emotional tendency of Weibo text and the construction of emotion dictionary, This paper presents an automatic construction method of emotion dictionary combining emoji. The method first uses the training data set provided by COAE2015 Task 1 to segment and remove the words, then obtains the affective words and their occurrence times in the positive and negative corpus, and then calculates their affective tendency by using PMI. Finally, the emotion dictionary is generated. (2) the influence of context view information on emotion tendency is studied, and a method of emotion tendency analysis based on context view information is proposed. First of all, we should define the context of the text. Since users are more or less influenced by the original text and their previous comments, this paper proposes a context-based approach to emotional orientation analysis and applies it to the emotional analysis of Weibo comments. In this method, the comment text is numbered according to the order of the comments, and the comment text is assigned the weight according to the order. Finally, the emotion dictionary is established. Finally, the emotional tendency of the algorithm is obtained. (3) A prototype system of Weibo emotional orientation analysis based on context view information is designed and implemented in the process of analyzing the emotional orientation of Weibo comment text. The corresponding functional modules are designed for each aspect, and a prototype system of Weibo emotional orientation analysis based on context view information is implemented. The system can mine and extract comment text in Weibo, analyze and process it, and provide users with intuitionistic emotional tendency.
【學(xué)位授予單位】：山東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.1

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