翻译
问题C：数据的财富
在其创建的在线市场中，亚马逊为客户提供了对购买进行评分和评价的机会。个人评级-称为“星级”-使购买者可以使用1（低评级，低满意度）到5（高评级，高满意度）的等级来表示他们对产品的满意度。此外，客户可以提交基于文本的消息（称为“评论”），以表达有关产品的更多意见和信息。其他客户可以根据这些评论提交有帮助或无帮助的等级（称为“帮助等级”），以协助他们自己的产品购买决策。公司使用这些数据来深入了解其参与的市场，参与的时间以及产品设计功能选择的潜在成功。
阳光公司计划在在线市场上推出和销售三种新产品：微波炉，婴儿奶嘴和吹风机。他们已聘请您的团队担任顾问，以识别过去客户提供的与其他竞争产品相关的评分和评论的关键模式，关系，度量和参数，以：
1）告知其在线销售策略；
2）识别潜在重要的设计特征，以提高产品的吸引力。 Sunshine Company过去曾使用数据为销售策略提供信息，但他们以前从未使用过这种特殊的组合和数据类型。 Sunshine Company特别感兴趣的是这些数据中的基于时间的模式，以及它们是否以有助于该公司制造成功产品的方式进行交互。
为了给您提供帮助，Sunshine的数据中心为您提供了该项目的三个数据文件：hair_dryer.tsv，microwave.tsv和pacifier.tsv。这些数据代表在数据指示的时间段内，在亚马逊市场上出售的微波炉，婴儿奶嘴和吹风机的客户提供的评分和评论。还提供了数据标签定义的词汇表。提供的数据文件包含您应用于此问题的唯一数据。
要求
1.分析提供的三个产品数据集，以使用数学证据来识别，描述和支持有意义的定量和/或定性模式，关系，量度和参数，这些数据将在有助于评估阳光的星级，评论和帮助等级之内和之间公司在其三项新的在线市场产品中取得了成功。
2.使用您的分析解决阳光公司市场总监的以下特定问题和要求：
a.一旦三种产品在在线市场上出售后，就可以根据评级和评论确定最能为Sunshine Company跟踪的数据度量。
b.在每个数据集中识别并讨论基于时间的度量和模式，这些度量和模式可能表明产品在在线市场中的声誉在上升或下降。
c.确定最能表明潜在成功或失败产品的基于文本的度量和基于评级的度量的组合。
d.特定星级会引起更多评论吗？例如，在看到一系列低星级评级之后，客户是否更有可能撰写某种类型的评论？
e.诸如“热情”，“失望”之类的基于文本的评论的特定质量描述符是否与评分水平紧密相关？
3.写一两页的信给阳光公司市场总监，总结您团队的分析和结果。包括针对您的团队最有信心地推荐给市场总监的结果的具体理由。
您的提交应包括：
•一页的摘要表
•目录
•一页到两页的信
•您的解决方案不超过20页，最多包含24页的摘要表，目录和两页的信件。
注意：参考列表和任何附录不计入页数限制，应在完成解决方案后出现。您不应使用未经版权法限制使用的未经授权的图像和材料。确保您引用了想法的来源和报告中使用的材料。
词汇表
帮助等级：表示在决定是否购买该产品时特定产品评论的价值。
奶嘴：一种橡胶或塑料的舒缓装置，通常为乳头状，提供给婴儿吸吮或咬咬。
审查：对产品的书面评估。
星级：在系统中给出的分数，该分数使人们可以对具有多个星级的产品进行评分。
附件：问题数据集
Problem_C_Data.zip提供的三个数据集包含产品用户评分和通过Amazon Simple Storage Service（Amazon S3）从Amazon客户评论数据集提取的评论。 hair_dryer.tsv微波炉.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.
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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?
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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
