论文标题
亚马逊假评论
Amazon Fake Reviews
论文作者
论文摘要
通常，有可疑的亚马逊评论似乎是过分积极的，或者是通过重复算法创建的。我通过语义分析与元数据（例如时间，单词选择和发布的用户）一起，通过语义分析来检测在亚马逊上的伪造评论。我首先提出了一些可能表明评论不是真实的实例，并构建了算法的外观。然后，我对算法进行了编码，并使用统计分析测试了它的准确性，并根据代码的六种质量对其进行了分析。
Often, there are suspicious Amazon reviews that seem to be excessively positive or have been created through a repeating algorithm. I moved to detect fake reviews on Amazon through semantic analysis in conjunction with meta data such as time, word choice, and the user who posted. I first came up with several instances that may indicate a review isn't genuine and constructed what the algorithm would look like. Then I coded the algorithm and tested the accuracy of it using statistical analysis and analyzed it based on the six qualities of code.
