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Let's take a closer look at football leagues: UEFA Champions League - list of games played by such teams as Chelsea, Manchester City, Liverpool, Ajax, etc. UEFA Conference League - among the popular names are Fenerbahce, Slavia, PAOK. ;Spain - La Liga;Coppa Italia;Russian Cup;Etc. We also want to note the variety of types of bets on the site. We recommend that you familiarize yourself with the rules of each of them before making a deal. In addition to football matches, dozens of varieties of sporting events are available to 1xBet customers. In total, the site has more than 40 sports disciplines with a diverse line of painting and with favorable odds. designer bags cyber monday
Amazon.com sells over 372 million products online (as of June 2017) and its online sales are so vast they affect store sales of other companies. But they don't just affect the amount that is sold by stores, but also what people buy in stores. It's a common habit of people to check Amazon reviews to see if they want to buy something in another store (or if Amazon is cheaper). For this reason, it's important to companies that they maintain a postive rating on Amazon, leading to some companies to pay non-consumers to write positive "fake" reviews. As a consumer, I have grown accustomed to reading reviews before making a final purchase decision, so my decisions are possibly being influenced by non-consumers. In reading about what clues can be used to identify fake reviews, I found may online resources say they are more likely to be generic and uninformative. This brings to mind several questions. Can low-quality reviews be used to potentially find fake reviews? Are products with mostly low-quality reviews more likely to be purchasing fake reviews? Can we identify people who are writing the fake reviews based on their quality? There are tens of thousands of words used in the reviews, so it is inefficient to fit a model all the words used. Instead, dimensionality reduction can be performed with Singular Value Decomposition (SVD). As I illustrate in a more detailed blog post, the SVD can be used to find latent relationships between features. The principal components are a combination of the words, and we can limit what components are being used by setting eigenvalues to zero. I limited my model to 500 components. usb, port, power, plugged, device, cable, adapter, switch... = Cables For higher numbers of reviews, lower rates of low-quality reviews are seen. At first sight, this suggests that there may be a relationship between more reviews and better quality reviews that's not necessarily due to popularity of the product. Popularity of a product would presumably bring in more low-quality reviewers just as it does high-quality reviewers. Perhaps products that more people review may be products that are easier to have things to say about. However, this does not appear to be the case. The top 5 review are the SanDisk MicroSDXC card, Chromecast Streaming Media Player, AmazonBasics HDMI cable, Mediabridge HDMI cable, and a Transcend SDHC card. Reviewers Let's take a deeper look at who is writing low-quality reviews. Here are the percent of low-quality reviews vs. the number of reviews a person has written. Next, in almost all of the low-quality reviewers, they wrote many reviews at a time. The likely reason people do so many reviews at once with no reviews for long periods of time is they simply don't write them as they buy things. The list of products in their order history builds up, and they do all the reviews at once. As a good example, here's a reviewer who was flagged as having 100% generic reviews. Note that the reviews are done in groupings by date, and while most of the reviews are either 4- or 5-stars, there is some variety. This isn't suspicious, but rather illustrates that people write multiple reviews at a time. designer bags cyber mondaychanel beige flap bag
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