Identifying Entity Aspects in Microblog Posts

Open Access
Authors
  • M.T. Bui
  • M. Breuss
Publication date 2012
Book title SIGIR'12: the proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval: August 12-16, 2012: Portland, Oregon, USA
ISBN
  • 9781450314725
Event SIGIR'12
Pages (from-to) 1089-1090
Publisher New York, NY: Association for Computing Machinery
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
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.
Document type Conference contribution
Language English
Published at https://doi.org/10.1145/2348283.2348483
Downloads
p1089-spina (Final published version)
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