Identifying Entity Aspects in Microblog Posts

Twitter aspects

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.

  • [PDF] D. Spina, E. Meij, M. de Rijke, A. Oghina, B. M. Thuong, and M. Breuss, “Identifying entity aspects in microblog posts,” in The 35th international acm sigir conference on research and development in information retrieval, 2012.
    [Bibtex]
    @inproceedings{SIGIR:2012:spina,
    Author = {Damiano Spina and Meij, Edgar and de Rijke, Maarten and Andrei Oghina and Bui Minh Thuong and Mathias Breuss},
    Booktitle = {The 35th International ACM SIGIR conference on research and development in Information Retrieval},
    Date-Added = {2012-05-03 22:17:17 +0200},
    Date-Modified = {2012-10-30 08:40:47 +0000},
    Series = {SIGIR 2012},
    Title = {Identifying Entity Aspects in Microblog Posts},
    Year = {2012}}

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