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 method such as TF.IDF are a strong baseline for the task, being significantly better than applying opinion-oriented methods and (ii) only considering terms tagged as nouns improves the results for all the methods analyzed.

More information on the dataset that we created (and used in this paper) can be found here.

[bibtex key=SIGIR:2012:spina]