Online Shopping Reviewers Are Not All That They Seem

837 Words Jun 17th, 2018 4 Pages
With the recent shift to web based communication, everything, including shopping, has gone online. With online shopping, consumers experience being in the comfort of their own home and they do not have to face bustling crowds. On the contrary, though, online shops allow for customer reviews on their items. The problem that these online stores are facing is that fake users are commenting on items to either boost or lower the ratings. Seventy percent of people trust online reviews (Fake Online Reviews). Online superstores like Amazon.com are popular because of their convenience. Amazon can post items themselves or independent stores can use their website to sell items. Since Amazon sells millions of items online each year, users have …show more content…
If the review sounds more like a press release or a legal document, it probably is not a legitimate one. The main point of this article by Ngo is that reviews that fall between are more reliable. People that really did purchase and use an item are more likely to talk about the reliability of an item and the overall value of the item Although one or two fake reviews will not affect the overall rating of an item, many of them can have a negative affect. Software developers have created programs to stop these fake reviewers from posting comments online. These programs have been programmed to tell the difference between the language used in a fake review and a legitimate one. Researchers sorted 2400 reviews written online and put them in categories of “spam, borderline spam, or non spam” (Marks). Researchers at Cornell University have attempted to create software that does the same thing. They found 400 false hotel reviews and 400 truthful ones and entered them in a database. The program’s job was to spot the difference between each review. The program got answered correctly 90 percent of the time. The average person can only spot the difference about 50 percent of the time. Creators of this software made it to work the same as plagiarism software. The creators also found that when a review is false, the review contains more verbs than a real one. The Cornell software developers’ next job is to try the software
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