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| Title: | 隱藏意見萃取--辨識多世代商品之關鍵特色
Latent Opinion Extraction: Identify Critical Product Features in Multiple Generations |
| Authors: | 林沛盈 |
| Contributors: | 唐揆
林沛盈 |
| Keywords: | 意見探勘
情緒分析
面相偵測
社會影響
遺失值填值
Opinion Mining
Sentiment Analysis
Aspect Identification
Social Influence
Missing Data Imputation |
| Date: | 2012 |
| Issue Date: | 2014-01-02 13:43:33 (UTC+8) |
| Abstract: | 隨著網路的普及，消費者將許多自身經驗撰寫成產品評論放上網站，使得消費者與廠商之間的資訊不對稱得以下降，同時產生了讓廠商無法忽視的口碑效應。根據兩項針對超過兩千名美國成年人的研究，有81%的網路使用者曾為一項商品上網進行至少一次的資料搜尋，其中有73%到87%的人表示網路評論對他們的購買意願產生了顯著的影響，特別是高涉入性產品。
在消費者與廠商之間的權力結構逐漸往消費者端傾斜的網路時代，廠商必須擁有在許多評論網站中快速彙整資料的能力。因此，針對評論做意見探勘，是非常重要的研究議題。而在意見探勘的領域中，若能分辨不同面相間的重要性差異，對廠商而言，可藉此判斷那些面相較能左右銷售量與使用者滿意度，本研究著重於探討消費者認為「重要面相」的研究。
然而，過去的研究較少討論到評論依據時間，後發表的評論會被前述評論影響的議題。本研究發現依據傳統的面相意見探勘，將會產生面相分數與整體分數不一致性的狀態，顯示消費者應有隱而未現的意見未被充分表達。本研究首度考慮了評論之間的關聯性，並以此發展填值方法。此外，本研究針對Amazon網站上Canon數位相機SX210、SX230，及SX260等三個世代數位相機的消費者評論提出GPA、MPA Matrix之分析架構。分析結果清楚指出該系列相機不同世代間的正向與負向面相。透過本研究的自動分析架構，廠商可以從數千筆消費者評論中，有效率且更精準的找到消費者滿意與需改善之面相。
A growing number of consumers have written product reviews to share their own experience on the Internet. The development decreases information asymmetry between consumers and manufactures and causes e-word of mouth effect that firms could not ignore. According to the survey of more than 2000 adults in the U.S., 81% of Internet users had searched for product information they planned to buy at least one time. Between 73% and 87% Internet users said the product reviews influenced their purchase intention, especially in high involvement products.
Consequently, it is essential for manufactures to have the ability to summarize thousands of consumer product reviews into useful information in a short time. Thus, review opinion mining becomes an important issue in the recent years. In the field of review opinion mining, it is critical for manufactures to differentiate product features in terms of their importance. According to the data from aspect opinion mining, manufactures can determine which product feature significantly influences sales volume and customer satisfaction. Therefore, our research focused on identifying “critical product features.”
We found existing studies did not address the time-effects on product reviews. That is, consumer review might be influenced by the foregoing reviews. The time-effects will cause inconsistent between the overall score and the feature score while the data based on the traditional aspect opinion mining method. Our research took the inconsistent situation into consideration, and developed an imputation method for features missing in reviews. In addition, we analyzed the sentiment polarity of Canon digital camera (SX210, SX230, SX260 generations) on Amazon with GPA, MPA Matrix. The results clearly identify the positive and negative features in different product generations. Using the automatic sentiment analysis framework we propose, manufactures could find the critical features that receive very favorable responses from consumers or need improvement in an efficient and more accurate way. |
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| Description: | 碩士
國立政治大學
企業管理研究所
100355026
101 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0100355026 |
| Data Type: | thesis |
| Appears in Collections: | [企業管理學系] 學位論文
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