Tags play a crucial role in CQA sites by facilitating organization, indexing and categorization of the entire post in a few words. The choice of tags determines the audience that is elicited upon to seek a response for any particular post. This could either lead to receiving an accurate response for the question or result in receiving no answers. The choice of tags, thus, directly determines the quality of the post as well as to a large extent the success of the CQA site itself. In this paper, we a present a novel approach to evaluate the choice of tags in any post. We perform tag network analysis to find relationship between tags. We then find the anomalous combination of tags by performing anomaly detection. We demonstrate the robustness of our approach by showing high AUC, in the range of 0.95 to 0.98, on four datasets from Stack Exchange, namely Ask Ubuntu, Server Fault, Super User and Software Engineering. © Springer Nature Switzerland AG 2019.