  Attackers create adversarial text to deceive both human perception and the
current AI systems to perform malicious purposes such as spam product reviews
and fake political posts. We investigate the difference between the adversarial
and the original text to prevent the risk. We prove that the text written by a
human is more coherent and fluent. Moreover, the human can express the idea
through the flexible text with modern words while a machine focuses on
optimizing the generated text by the simple and common words. We also suggest a
method to identify the adversarial text by extracting the features related to
our findings. The proposed method achieves high performance with 82.0% of
accuracy and 18.4% of equal error rate, which is better than the existing
methods whose the best accuracy is 77.0% corresponding to the error rate 22.8%.
