Existing deep supervised image hashing approaches rely on substantial labeled image data, which is very difficult to be widely applied in reality. By utilizing tags associated with images as the supervision information, a context-aware deep weakly supervised image hashing method was proposed. The method enhanced the image region representations by adaptively capturing the relevant context information of image region features, and raised the discrimination of the learnt hash codes by introducing a discrimination loss. Extensive experiments on two public datasets show the effectiveness of the method.