Title: Alternative Adversarial Sampling Attack on Text and Sentiment Classification • Study and evaluate existing representations and classifications on text and document. • Study adversary model on adversarial method towards machine learning algorithm. • Build and evaluate similar existing attack method. • Simulate practical and realistic scene of adversarial attack on classification model. • Build Machine Learning model on NLP classification task. • Develop new method of word transformer for word-level attack. • Optimize influential word sorting by precedency score. • Achieve best results of attack efficacy on Bi-directional LSTM and BERT. • Achieve best results in terms of perturbation rate.