翻譯
問題C：數據的財富
在其創建的在線市場中，亞馬遜爲客戶提供了對購買進行評分和評價的機會。個人評級-稱爲“星級”-使購買者可以使用1（低評級，低滿意度）到5（高評級，高滿意度）的等級來表示他們對產品的滿意度。此外，客戶可以提交基於文本的消息（稱爲“評論”），以表達有關產品的更多意見和信息。其他客戶可以根據這些評論提交有幫助或無幫助的等級（稱爲“幫助等級”），以協助他們自己的產品購買決策。公司使用這些數據來深入瞭解其參與的市場，參與的時間以及產品設計功能選擇的潛在成功。
陽光公司計劃在在線市場上推出和銷售三種新產品：微波爐，嬰兒奶嘴和吹風機。他們已聘請您的團隊擔任顧問，以識別過去客戶提供的與其他競爭產品相關的評分和評論的關鍵模式，關係，度量和參數，以：
1）告知其在線銷售策略；
2）識別潛在重要的設計特徵，以提高產品的吸引力。 Sunshine Company過去曾使用數據爲銷售策略提供信息，但他們以前從未使用過這種特殊的組合和數據類型。 Sunshine Company特別感興趣的是這些數據中的基於時間的模式，以及它們是否以有助於該公司製造成功產品的方式進行交互。
爲了給您提供幫助，Sunshine的數據中心爲您提供了該項目的三個數據文件：hair_dryer.tsv，microwave.tsv和pacifier.tsv。這些數據代表在數據指示的時間段內，在亞馬遜市場上出售的微波爐，嬰兒奶嘴和吹風機的客戶提供的評分和評論。還提供了數據標籤定義的詞彙表。提供的數據文件包含您應用於此問題的唯一數據。
要求
1.分析提供的三個產品數據集，以使用數學證據來識別，描述和支持有意義的定量和/或定性模式，關係，量度和參數，這些數據將在有助於評估陽光的星級，評論和幫助等級之內和之間公司在其三項新的在線市場產品中取得了成功。
2.使用您的分析解決陽光公司市場總監的以下特定問題和要求：
a.一旦三種產品在在線市場上出售後，就可以根據評級和評論確定最能爲Sunshine Company跟蹤的數據度量。
b.在每個數據集中識別並討論基於時間的度量和模式，這些度量和模式可能表明產品在在線市場中的聲譽在上升或下降。
c.確定最能表明潛在成功或失敗產品的基於文本的度量和基於評級的度量的組合。
d.特定星級會引起更多評論嗎？例如，在看到一系列低星級評級之後，客戶是否更有可能撰寫某種類型的評論？
e.諸如“熱情”，“失望”之類的基於文本的評論的特定質量描述符是否與評分水平緊密相關？
3.寫一兩頁的信給陽光公司市場總監，總結您團隊的分析和結果。包括針對您的團隊最有信心地推薦給市場總監的結果的具體理由。
您的提交應包括：
•一頁的摘要表
•目錄
•一頁到兩頁的信
•您的解決方案不超過20頁，最多包含24頁的摘要表，目錄和兩頁的信件。
注意：參考列表和任何附錄不計入頁數限制，應在完成解決方案後出現。您不應使用未經版權法限制使用的未經授權的圖像和材料。確保您引用了想法的來源和報告中使用的材料。
詞彙表
幫助等級：表示在決定是否購買該產品時特定產品評論的價值。
奶嘴：一種橡膠或塑料的舒緩裝置，通常爲乳頭狀，提供給嬰兒吸吮或咬咬。
審查：對產品的書面評估。
星級：在系統中給出的分數，該分數使人們可以對具有多個星級的產品進行評分。
附件：問題數據集
Problem_C_Data.zip提供的三個數據集包含產品用戶評分和通過Amazon Simple Storage Service（Amazon S3）從Amazon客戶評論數據集提取的評論。 hair_dryer.tsv微波爐.tsv pacifier.tsv
原文
Problem C: A Wealth of Data
In the online marketplace it created, Amazon provides customers with an opportunity to rate and review purchases. Individual ratings - called “star ratings” – allow purchasers to express their level of satisfaction with a product using a scale of 1 (low rated, low satisfaction) to 5 (highly rated, high satisfaction). Additionally, customers can submit text-based messages – called “reviews” – that express further opinions and information about the product. Other customers can submit ratings on these reviews as being helpful or not – called a “helpfulness rating” – towards assisting their own product purchasing decision. Companies use these data to gain insights into the markets in which they participate, the timing of that participation, and the potential success of product design feature choices.
Sunshine Company is planning to introduce and sell three new products in the online marketplace: a microwave oven, a baby pacifier, and a hair dryer. They have hired your team as consultants to identify key patterns, relationships, measures, and parameters in past customersupplied ratings and reviews associated with other competing products to 1) inform their online sales strategy and 2) identify potentially important design features that would enhance product desirability. Sunshine Company has used data to inform sales strategies in the past, but they have not previously used this particular combination and type of data. Of particular interest to Sunshine Company are time-based patterns in these data, and whether they interact in ways that will help the company craft successful products.
To assist you, Sunshine’s data center has provided you with three data files for this project: hair_dryer.tsv, microwave.tsv, and pacifier.tsv. These data represent customer-supplied ratings and reviews for microwave ovens, baby pacifiers, and hair dryers sold in the Amazon marketplace over the time period(s) indicated in the data. A glossary of data label definitions is provided as well. THE DATA FILES PROVIDED CONTAIN THE ONLY DATA YOU SHOULD USE FOR THIS PROBLEM.
Requirements 1. Analyze the three product data sets provided to identify, describe, and support with mathematical evidence, meaningful quantitative and/or qualitative patterns, relationships, measures, and parameters within and between star ratings, reviews, and helpfulness ratings that will help Sunshine Company succeed in their three new online marketplace product offerings.
-
Use your analysis to address the following specific questions and requests from the Sunshine Company Marketing Director: a. Identify data measures based on ratings and reviews that are most informative for Sunshine Company to track, once their three products are placed on sale in the online marketplace. b. Identify and discuss time-based measures and patterns within each data set that might suggest that a product’s reputation is increasing or decreasing in the online marketplace. c. Determine combinations of text-based measure(s) and ratings-based measures that best indicate a potentially successful or failing product.
d. Do specific star ratings incite more reviews? For example, are customers more likely to write some type of review after seeing a series of low star ratings? e. Are specific quality descriptors of text-based reviews such as ‘enthusiastic’, ‘disappointed’, and others, strongly associated with rating levels? -
Write a one- to two-page letter to the Marketing Director of Sunshine Company summarizing your team’s analysis and results. Include specific justification(s) for the result that your team most confidently recommends to the Marketing Director.
Your submission should consist of:
• One-page Summary Sheet
• Table of Contents
• One- to Two-page Letter
• Your solution of no more than 20 pages, for a maximum of 24 pages with your summary sheet, table of contents, and two-page letter.
Note: Reference List and any appendices do not count toward the page limit and should appear after your completed solution. You should not make use of unauthorized images and materials whose use is restricted by copyright laws. Ensure you cite the sources for your ideas and the materials used in your report.
Glossary
Helpfulness Rating: an indication of how valuable a particular product review is when making a decision whether or not to purchase that product.
Pacifier: a rubber or plastic soothing device, often nipple shaped, given to a baby to suck or bite on.
Review: a written evaluation of a product.
Star Rating: a score given in a system that allows people to rate a product with a number of stars.
Attachments: The Problem Datasets
Problem_C_Data.zip The three data sets provided contain product user ratings and reviews extracted from the Amazon Customer Reviews Dataset thru Amazon Simple Storage Service (Amazon S3). hair_dryer.tsv microwave.tsv pacifier.tsv