Information Retrieval Journal

, Volume 18, Issue 6, pp 530–558

OpinoFetch: a practical and efficient approach to collecting opinions on arbitrary entities


DOI: 10.1007/s10791-015-9272-0

Cite this article as:
Ganesan, K. & Zhai, C. Inf Retrieval J (2015) 18: 530. doi:10.1007/s10791-015-9272-0


The abundance of opinions on the Web is now becoming a critical source of information in a variety of application areas such as business intelligence, market research and online shopping. Unfortunately, due to the rapid growth of online content, there is no one source to obtain a comprehensive set of opinions about a specific entity or a topic, making access to such content severely limited. While previous works have been focused on mining and summarizing online opinions, there is limited work on exploring the automatic collection of opinion content on the Web. In this paper, we propose a lightweight and practical approach to collecting opinion containing pages, namely review pages on the Web for arbitrary entities. We leverage existing Web search engines and use a novel information network called the FetchGraph to efficiently obtain review pages for entities of interest. Our experiments in three different domains show that our method is more effective than plain search engine results and we are able to collect entity specific review pages efficiently with reasonable precision and accuracy.


Opinion crawling Opinion aggregation Opinion analysis Review crawling Opinion collection Review aggregation 

Funding information

Funder NameGrant NumberFunding Note
NSF Office of the Director
  • None

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.University of Illinois at Urbana ChampaignUrbanaUSA

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