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博碩士論文 etd-0703122-175621 詳細資訊
Title page for etd-0703122-175621
論文名稱
Title
餐廳評論中話題、情緒、與星等相關性之研究—以Yelp 評論為例
The Correlation among Topics, Emotions, and Stars on Restaurant Reviews- Taking Yelp's Reviews as an Example
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
121
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2022-06-29
繳交日期
Date of Submission
2022-08-03
關鍵字
Keywords
使用者生成內容、電子口碑、情緒分析、內容分析、多元回歸分析
User-generated content, Electronic word-of-mouth, Sentiment analysis, Content analysis, Multiple Regression Analysis
統計
Statistics
本論文已被瀏覽 263 次,被下載 46
The thesis/dissertation has been browsed 263 times, has been downloaded 46 times.
中文摘要
隨著使用者生成媒體興起,許多透過使用者生成內容做為資訊及經驗的傳遞,幫助用戶藉由這些內容去找出符合自己需求的產品及服務,而像是旅遊、酒店或餐飲業都屬於體驗產品,此類的評論網站所包含的網路評論又可被稱為電子口碑,這些電子口碑會影響消費者做出購買決策,因此網路評論成為現在許多人選擇餐廳的參考準則,另一方面,網路評論也是衡量店家的重要指標,餐廳管理者可以透過網路評論瞭解自家餐廳的優勢及需要補足的部分。
本研究以Yelp網站之餐廳評論作為例,篩選出內華達州89109地區,將餐廳區分為各種類型,並將其網路評論透過情緒及話題分類處理,再切割2015至2019年的時間區段,第一部分則是分別去情緒分析以及10種話題和星等的相關性,藉此找出各餐廳類型的差異。第二部分則透過多元回歸分析看每兩年的星等差異,以及影響星等的話題是否會因不同餐廳類型而有所差異。本研究發現各餐廳的對於10話題的情緒表現差異不大,多數類型的餐廳其服務方式、態度和餐廳吸引力都偏向正面情緒,價格及整體價值則較容易有負面情緒;而影響餐廳星等的話題也都蠻相似的,只有少數像是休閒、幼稚詼諧或情感的話題,較適合在歐洲類型的餐廳評論中出現。
Abstract
With the rise of user-generated media, many users use user-generated content as the transmission of information and experience to help them find products and services that meet their needs. Tourism, hospitality and catering are all experience products. Their online reviews contained in such review sites can also be called electronic word-of-mouth. These electronic word-of-mouth will influence consumers to make purchasing decisions, so online reviews have become the reference criteria for many people to choose restaurants. On the other hand, online reviews are also an important indicator to measure stores. Restaurant managers can use online reviews to understand the advantages of their own restaurants and the parts that need to be supplemented.
Taking restaurant reviews on Yelp website as an example, this study screened out the 89109 area in Nevada, divided restaurants into various types, and processed their online reviews through sentiment and topic classification, and then cut the time period from 2015 to 2019. The first part is to analyze the sentiment and the correlation between 10 topics and stars separately, so as to find out the differences of each restaurant type. The second part uses multiple regression analysis to look at the difference in star ratings every two years, and whether the topics that affect star ratings vary by restaurant type. This study found that there was little difference in the emotional performance of restaurants on the 10 topics. Most types of restaurants tend to have positive emotions in their service methods, attitudes and restaurant attractiveness, while price and overall value are more likely to have negative emotions; The topics are also quite similar, with only a few topics like casual, childish witty, or emotional that are more suitable for European-type restaurant reviews.
目次 Table of Contents
論文審定書……………………………………………………………………………………………………………………………… i
中文摘要……………………………………………………………………………………………………………………………..….ii
Abstract……………………………………………………………………………………………………………..……………..…… iii
目錄……………………………………………………………………………………………………………………………….……….iv
圖次………………………………………………………………………..…………………………………………………………..…..v
表次………………………………………………………………………..…………….…………………………………………….. viii
第一章 緒論 1
第一節 研究背景 1
第二節 研究目的 2
第三節 研究問題 3
第四節 研究架構 4
第二章 文獻探討 5
第一節 網路評論 5
第二節 餐廳滿意度屬性 6
第三節 餐廳滿意度的分析方法 7
第四節 Empath方法 9
第三章 研究方法 11
第一節 資料來源 11
第二節 資料處理 11
第三節 分析方法 15
第四節 研究流程 16
第四章 研究結果 17
第一節 各類型餐廳的用餐屬性差異 17
第二節 各類型餐廳影響星等的話題變化 50
第五章 結論與建議 103
第一節 研究結論 103
第二節 研究限制與未來研究方向 104
參考文獻 105

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二、 網路資源
M. L. Jockers. (2015). Syuzhet: Extraction of sentiment and sentiment-based plot arcs from text. Retrieved from https://github.com/mjockers/syuzhet
Restaurant Engine. (2017). Find Out What Your Patrons Think – 7 Restaurant Review Sites Owners Can Monitor. Retrieved from https://restaurantengine.com/restaurant-review-sites/
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