Online reputation management is about monitoring and handling the public image of entities (such as companies) on the Web. An important task in this area is identifying "aspects" of the entity of interest (such as products, services, competitors, key people, etc.) given a stream of microblog posts referring to the entity. In this paper we compare different IR techniques and opinion target identification methods for automatically identifying aspects and find that (i) simple statistical methods such as TF.IDF are a strong baseline for the task, significantly outperforming opinion-oriented methods, and (ii) only considering terms tagged as nouns improves the results for all the methods analyzed.