Sentiment analysis of short social media texts is a challenging task due to limited contextual information and noise in texts. We present a deep convolutional model that utilizes unsupervised pre-trained word embeddings to detect offensive texts. Unfortunately, the model cannot outperform the baseline model in task-1 of the Germeval Task 2018 in terms of the F1-measure.