This study explores the potential of using tweets to predict article retractions, by analyzing the Twitter mention data of retracted articles as the treatment group and unretracted articles that were matched as a control group. The results show that tweets could predict article retractions with an accuracy of 57%-60% by machine learning models. Sentiment analysis is not effective in predicting article retractions. The study sheds light on a novel method of detecting scientific misconduct in the early stage.