Abstract
In recent years, Instagram has become one of top 15 online social networks. However, popularity of Instagram also causes advertisement and spam posts flooding. Therefore, it is necessary to build a spam detection model to decrease number of spam posts in Instagram. We present a scheme applying feature-based method and supervised learning technique to detect spam posts from Instagram. We use K-fold cross validation to find best pair of supervised learning model and parameters of the model and accuracy of our best model is 96.27%.