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Evaluating the Usefulness of Sentiment Information for Focused Crawlers (1309.7270v1)

Published 27 Sep 2013 in cs.IR and cs.CL

Abstract: Despite the prevalence of sentiment-related content on the Web, there has been limited work on focused crawlers capable of effectively collecting such content. In this study, we evaluated the efficacy of using sentiment-related information for enhanced focused crawling of opinion-rich web content regarding a particular topic. We also assessed the impact of using sentiment-labeled web graphs to further improve collection accuracy. Experimental results on a large test bed encompassing over half a million web pages revealed that focused crawlers utilizing sentiment information as well as sentiment-labeled web graphs are capable of gathering more holistic collections of opinion-related content regarding a particular topic. The results have important implications for business and marketing intelligence gathering efforts in the Web 2.0 era.

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Authors (4)
  1. Tianjun Fu (1 paper)
  2. Ahmed Abbasi (20 papers)
  3. Daniel Zeng (18 papers)
  4. Hsinchun Chen (15 papers)

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