Chinese readers should check out Wendy’s great post 来自谷歌首页的圣诞祝福!
Combining 17 different images together, Google’s prime Doodler Micheal Lopez spent 250 hours to create their latest Christmas-card masterpiece, a beautiful, abstract rendition approximating the Google logo. According to the WSJ, Chief-Doddler Lopez said, “We want to end the year with a bang.”
As seen on Google’s homepage
Each of the 17 images represents an image of holiday cheer, a sort of cultural Christmas card. So, the entire Google represents a global merry Christmas! Below, I will explode each image into its component links.
What is Amazon Vine?
For those not in the know, Amazon describes their Vine customer review program as:
Amazon Vine™ is a program that enables a select group of Amazon customers to post opinions about new and pre-release items to help their fellow customers make educated purchase decisions. Customers are invited to become Amazon Vine™ Voices based on the trust they have earned in the Amazon community for writing accurate and insightful reviews. Amazon provides Amazon Vine™ members with free copies of products that have been submitted to the program by vendors. Amazon does not influence the opinions of Amazon Vine™ members, nor do we modify or edit their reviews.
I disagree. I believe that Amazon Vine fundamentally biases reviewers. Sending customers free merchandise and require them to write about it should naturally produce positive bias. After all, if the book sucked, it was free, right?
Before we start, I would like to reference a number of existing article about Amazon Vine which may be relevant. First, in this Hacker News post, a member comments: “It is awfully tempting to start reviewing products with glowing praise in hopes that you will soon start getting free stuff in the mail.” Jon Bischke complains in Why Amazon Vine is a Threat Worth Talking About that “We’re being shown reviews for people who didn’t pay a dime for a product adjacent to people who shelled out their hard earned cash to pay for the product.” AvidBookReader promises that he’ll “just have to ignore these reviews, too.”
What’s the Data?
Note: between starting the idea for this research, and executing the idea, Amazon removed support from their API for reviews, making it many times more annoying to gather the necessary data. Instead of using a sanctioned means, I have resorted to scraping, which is unfortunate.
The dataset I am analyzing consists of 134,881 reviews gathered from the top 20 items of each category in the Amazon Best Sellers list. Each review consists of a star rating (out of five) and a boolean indicating if it is an Amazon vine review or not. Items which lack any Vine reviews at all were excluded, which includes the entire Industrial & Scientific section. A first pass through the data turns up 130,077 regular reviews, and 4,804 amazon vine reviews. Across all items, they fall into the following distribution:
Some categories do not have many Vine samples, but almost 16% of Software reviews are from the Vine program, with the following distribution:
Here we can visually observe that the Vine reviews appear to be skewed away from the 1/2-star reviews towards the 4/5-star area. To prove this, we will perform Chi-square significance tests on each category to try to prove that vine reviews significantly differ from regular reviews. We will use the alpha-cutoff of .5 (95%), as a standard measure. If you like, you can download the full results: Amazon Vine – Chi Squared Results (PDF).
In the Software category, we see some significant differences between Vine and regular Amazon reviews:
Here we get twice as many 4-star ratings as expected, and only about a quarter as many 1-star ratings, showing statistically significant Vine-inflation. The Chi Square statistic of 77 exceeds the critical area of 9.5, so we know that there’s a 0% chance of having a bad sample.
In the Office Products category, we see the opposite:
There is no statistically significant variance between the vine and regular reviews. It’s a coin toss if the vine reviews here are different or not from the regular Amazon reviews.
The following categories, totaling 58% of reviews (77,762), showed significant differences between Vine and Regular reviews:
Amazon Video On Demand (5313), Automotive (2107), Beauty (4106), Books (5556), Camera & Photo (2655), Cell Phones & Accessories (5678), Grocery & Gourmet Food (5998), Health & Personal Care (8205), Home & Garden (11382), Home Improvement (2364), Magazines (2600), Movies & TV (10490), Music (3652), Software (1761), Toys & Games (1240), Video (4655)
These categories, totaling 42% of reviews (57,136) did not:
Baby (4879), Clothing (1222), Computer & Accessories (651), Electronics (24205), Industrial & Scientific (127), Jewelry (924), Kitchen & Dining (11382), Musical Instruments (1701), Office Products (877), Patio, Lawn & Garden (2588), Shoes (1001), Sports & Outdoors (3208), Video Games (3729), Watches (642)
This roughly corresponds to the high-low density partition of categories by percentage of Amazon Vine reviews. The significant categories enjoy an average Vine review rate of 5.6% of the total reviews, while the insignificant categories average just 1.9% vine reviews. So, I can attribute the significance either to insufficient Vine data in the categories I sample, or a network effect where more Vine reviews produce the desired bias. The following graph, of significance in distribution of reviews, to the percentage of vine data in the reviews, supports this theory:
When we look at the categories which display bias, we arrive at the following distribution of reviews:
We see a significant skew. Overall, we see that the Amazon Vine reviews average a 4.31, while the non-Vine reviews average 4.26. Standard deviations are 0.99 for Vine, compared to 1.22 for non-Vine. So the overall averages are not affected by the bias present in Amazon vine reviews. Rather, it is the distribution itself that is affected. Vine reviewers give out fewer 5s than regular reviewers, while giving more 4s, and fewer 1s. In some sense, we can say that the Vine program functions as a range compression in the review-space.
Given these facts, does the Amazon Vine program bias reviews? No. In fact, it can be thought of as a statistical reviews moderator. While the Vine reviews are differently distributed (compressed), they still hover about the same averages. And it’s the averages that inform the next consumer on the shopping site.
Note: I am not a Statistician, so if I really screwed up some concepts here, please leave a comment. I have the raw data, and can redo analysis if warranted.
If you go to apple/iTunes you can checkout their new font/styling for iTunes 10, a sort of chromed gradient that looks like it was produced in Microsoft Word. Here’s the logo and type on Apple’s website:
And here’s a 30s mockup in Microsoft Word using their famous “Word Art” tool:
You would think they would spend a little more time on this, but perhaps the iTunes 10 team was too busy making iTunes suck more on Windows, and this is subtle Microsoft jab, or else building the useless social network Pring. People have also complained that the icon is horrible and suggested alternatives. Oh well, Apple.