【摘要】：房價(jià)滿意度作為衡量社會發(fā)展的一個(gè)重要指標(biāo)，正在引起社會的廣泛關(guān)注但是由于難以量化數(shù)據(jù)收集繁瑣時(shí)效性弱等困難，相關(guān)研究無法深入伴隨著互聯(lián)網(wǎng)技術(shù)的不斷進(jìn)步，在線討論平臺的快速發(fā)展壯大，如新浪微博主題論壇等，民眾利用這些新興渠道暢所欲言，在其中就包括與房價(jià)高度相關(guān)的大量言論信息這些信息背后就是民眾對于房價(jià)的情感態(tài)度，是民眾對于房價(jià)滿意度的一種碎片式表達(dá)，這些碎片化的信息中就包含著民眾對于房價(jià)的滿意程度房價(jià)微博情感分類，是指利用數(shù)據(jù)挖掘的方法，對大數(shù)量級的房價(jià)微博進(jìn)行情感傾向信息識別，借此為房價(jià)滿意度研究提供支持 本文以北京房價(jià)微博作為直接研究對象首先，采集了以北京房價(jià)為關(guān)鍵字的，2011年1月到2014年1月這個(gè)時(shí)間段內(nèi)的所有微博數(shù)據(jù)，其中有效數(shù)據(jù)共計(jì)59957條然后，基于N-Gram語言模型構(gòu)建情感傾向分類器通過不斷優(yōu)化訓(xùn)練集使分類準(zhǔn)確率達(dá)到95%以上最后，在準(zhǔn)確率達(dá)到要求的前提下，，挖掘出蘊(yùn)含在房價(jià)微博中民眾對于房價(jià)的情感傾向 依據(jù)本文前兩章所取得的成果，對民眾滿意度與房價(jià)之間的關(guān)系進(jìn)行實(shí)證分析首先，利用基于N-Gram語言模型的情感分類器對每月的北京房價(jià)微博數(shù)據(jù)進(jìn)行情感傾向識別，計(jì)算情緒得分，借此量化民眾對于房價(jià)的滿意程度然后，聯(lián)系北京市每月的新建住宅銷售價(jià)格指數(shù)這一相對值住宅平均銷售價(jià)格這一絕對值，以及推算出的每月住宅銷售價(jià)格增長率這三個(gè)變量進(jìn)行統(tǒng)計(jì)分析最終，統(tǒng)計(jì)分析結(jié)果表明民眾對于房價(jià)的滿意程度受到房價(jià)絕對值和相對值的顯著影響，且房價(jià)相對值對其影響程度更強(qiáng)，相比于房價(jià)絕對值進(jìn)而，聯(lián)系所查閱文獻(xiàn)與相關(guān)理論進(jìn)行模型結(jié)果的解釋最后，本研究利用所取得的成果，聯(lián)系房地產(chǎn)實(shí)踐領(lǐng)域，給予提高房地產(chǎn)領(lǐng)域民眾滿意度的建議本研究為中文文本情感傾向自動識別在房地產(chǎn)領(lǐng)域進(jìn)行了新的探索，為政府制定公共政策提供數(shù)據(jù)支持和理論基礎(chǔ)，也為學(xué)者繼續(xù)研究文本情感傾向提供很好的思路
[Abstract]:As an important index to measure social development, house price satisfaction is attracting wide attention of the society. However, due to the difficulty of quantifying data collection, such difficulties as tedious and weak timeliness, the related research can not go deep with the continuous progress of Internet technology. With the rapid development of online discussion platforms, such as the Sina Weibo theme Forum, people use these new channels to speak freely. Among them is a large amount of speech information that is highly relevant to house prices. Behind this information is the public's emotional attitude towards housing prices, a fragmented expression of people's satisfaction with housing prices. These pieces of information contain the people's satisfaction with the housing prices, Weibo's emotional classification of housing prices, which refers to the use of data mining methods to identify the affective tendency information of the house prices in the order of magnitude, Weibo. In order to provide support for the research on the degree of house price satisfaction, this paper takes Weibo as the direct research object. Firstly, we collect all Weibo data in the period from January 2011 to January 2014, which is based on the key word of housing price in Beijing. There are 59957 valid data, and then, based on the N-Gram language model, the classification accuracy of emotion tendency classifier is over 95% by continuously optimizing the training set. Excavating the emotion tendency of the people to the house price in Weibo of housing price, according to the results obtained in the first two chapters of this paper, the relationship between the satisfaction of the people and the house price is analyzed empirically, first of all, The emotion classifier based on N-Gram language model is used to identify the emotion tendency of Weibo data of housing price in Beijing every month, to calculate the emotion score, so as to quantify the people's satisfaction with the house price, and then, Connecting with the absolute value of the monthly sales price index of newly built residential buildings in Beijing, the absolute value of the average residential sales price, and the calculated monthly residential sales price growth rate, the three variables are statistically analyzed. The results of statistical analysis show that the satisfaction of the public with the house price is significantly affected by the absolute and relative value of the house price, and the relative value of the house price has a stronger impact on it, compared with the absolute value of the house price, With reference to literature and related theories to explain the results of the model finally, this study uses the results obtained, the real estate practice field, Suggestions for improving the satisfaction of people in Real Estate this study provides a new exploration for automatic identification of emotional tendencies in Chinese texts and provides data support and theoretical basis for the government to formulate public policies. It also provides a good way for scholars to continue to study the emotional tendency of text.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：G206;F299.23

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