This paper presents the system that has been submitted to the multilingual gender biased and communal language identification shared task by BFCAI team. The proposed model used Support Vector Machines (SVMs) as a classification algorithm. The features have been extracted using TF/IDF model with unigram and bigram. The proposed model is very simple and there are no external resources are needed to build the model.