本文選題：在線評(píng)論 + 有用性　； 參考：《吉林大學(xué)》2017年碩士論文

【摘要】：根據(jù)中國互聯(lián)網(wǎng)絡(luò)信息中心(CNNIC)發(fā)布《2015年中國網(wǎng)絡(luò)購物市場研究報(bào)告》顯示,截至2015年12月,中國網(wǎng)絡(luò)購物市場交易總次數(shù)達(dá)256億次,年度人均交易次數(shù)62次。伴隨著網(wǎng)絡(luò)購物的蓬勃發(fā)展,購物信息巨增,研究表明,相比于商家展示的信息,消費(fèi)者更愿意相信網(wǎng)絡(luò)在線評(píng)論,也就是網(wǎng)絡(luò)口碑。當(dāng)前多數(shù)網(wǎng)絡(luò)購物平臺(tái)都擁有比較完善的售后評(píng)價(jià)系統(tǒng),方便消費(fèi)者對(duì)商品進(jìn)行信息反饋,以供后續(xù)買家參考。但是伴隨著電子商務(wù)的蓬勃發(fā)展,評(píng)價(jià)信息的數(shù)量呈現(xiàn)出指數(shù)級(jí)的增長,消費(fèi)者在面對(duì)海量信息時(shí),如何快速的識(shí)別可靠的信息,提高信息判斷的準(zhǔn)確性是一個(gè)亟待解決的問題。此種現(xiàn)象逐漸引起了國內(nèi)外學(xué)者的關(guān)注,相關(guān)研究成果如雨后春筍,但目前學(xué)者的研究多數(shù)集中在評(píng)論識(shí)別、評(píng)論有用性影響因素等方面,對(duì)評(píng)論的排序過濾問題的關(guān)注度較少。針對(duì)目前的現(xiàn)狀,本文從評(píng)論的有用性過濾排序入手,旨在將維度更豐富的評(píng)論信息優(yōu)先呈現(xiàn)給消費(fèi)者,提高消費(fèi)者信息有用性感知。本文通過查閱以往文獻(xiàn),梳理在線評(píng)論有用性影響因素,構(gòu)建本文的概念模型,通過定量研究方法對(duì)相關(guān)指標(biāo)進(jìn)行量化處理,并采用模糊層次分析法對(duì)三大指標(biāo)進(jìn)行權(quán)重的確定,并結(jié)合數(shù)據(jù)包絡(luò)分析法對(duì)在線評(píng)論進(jìn)行過濾排序,最終采用實(shí)證法進(jìn)行驗(yàn)證。實(shí)驗(yàn)證明,本研究排序方法可靠,排序結(jié)果比較理想,能較好的處理當(dāng)前在線評(píng)論大量冗余的問題,可明顯提高消費(fèi)者的在線評(píng)論有用性感知。對(duì)用戶有效識(shí)別可靠信息,提高信息判斷的準(zhǔn)確性具有一定的理論與實(shí)踐意義。
[Abstract]:According to the 2015 China online Shopping Market Research report released by the China Internet Network Information Center (CNNIC), the total number of transactions in China's online shopping market reached 25.6 billion by December 2015, with 62 transactions per person per year. With the rapid development of online shopping, shopping information has increased dramatically. Research shows that consumers are more willing to believe online reviews, that is, online word-of-mouth, than the information displayed by merchants. At present, most online shopping platforms have relatively perfect after-sale evaluation system, which is convenient for consumers to carry out information feedback for subsequent buyers. However, with the rapid development of electronic commerce, the quantity of evaluation information is increasing exponentially. How to identify reliable information quickly when consumers face mass information. It is an urgent problem to improve the accuracy of information judgment. This phenomenon has gradually attracted the attention of scholars at home and abroad, related research results such as springing up, but at present, most of the scholars focus on the identification of comments, comment usefulness factors, and so on. The problem of sorting and filtering comments is less concerned. In view of the present situation, this paper starts with the filtering and sorting of the usefulness of comments, aiming at giving priority to the more abundant comment information to consumers and improving consumers' perception of the usefulness of information. This paper reviews the previous literatures, combs the influencing factors of online review usefulness, constructs the conceptual model of this paper, and quantifies the relevant indicators by quantitative research methods. The fuzzy analytic hierarchy process (FAHP) is used to determine the weights of the three indexes, and the data envelopment analysis method is used to filter and sort the online comments. Finally, the empirical method is used to verify them. The experimental results show that the method is reliable and the sorting result is ideal. It can deal with the redundant problem of online reviews and improve consumers' perception of online comment usefulness. It is of theoretical and practical significance for users to identify reliable information and improve the accuracy of information judgment.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F724.6;F224

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