We study the problem of opinion question generation from sentences with the help of community-based question answering systems. For this purpose, we use a sequence to sequence attentional model, and we adopt coverage mechanism to prevent sentences from repeating themselves. Experimental results on the Amazon question/answer dataset show an improvement in automatic evaluation metrics as well as human evaluations from the state-of-the-art question generation systems.