Leveraging the crowd to improve feature-sentiment analysis of user reviews

Shih Wen Huang, Pei Fen Tu, Wai-Tat Fu, Mohammad Amanzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Crowdsourcing and machine learning are both useful techniques for solving difficult problems (e.g., computer vision and natural language processing). In this paper, we propose a novel method that harnesses and combines the strength of these two techniques to better analyze the features and the sentiments toward them in user reviews. To strike a good balance between reducing information overload and providing the original context expressed by review writers, the proposed system (1) allows users to interactively rank the entities based on feature-rating, (2) automatically highlights sentences that are related to relevant features, and (3) utilizes implicit crowdsourcing by encouraging users to provide correct labels of their own reviews to improve the feature-sentiment classifier. The proposed system not only helps users to save time and effort to digest the often massive amount of user reviews, but also provides real-time suggestions on relevant features and ratings as users generate their own reviews. Results from a simulation experiment show that leveraging on the crowd can significantly improve the feature-sentiment analysis of user reviews. Furthermore, results from a user study show that the proposed interface was preferred by more participants than interfaces that use traditional noun-adjective pair summarization, as the current interface allows users to view feature-related information in the original context.

Original languageEnglish (US)
Title of host publicationIUI 2013 - Proceedings of the 18th International Conference on Intelligent User Interfaces
Number of pages11
StatePublished - Mar 19 2013
Event18th International Conference on Intelligent User Interfaces, IUI 2013 - Santa Monica, CA, United States
Duration: Mar 19 2013Mar 22 2013

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI


Other18th International Conference on Intelligent User Interfaces, IUI 2013
CountryUnited States
CitySanta Monica, CA


  • Crowdsourcing
  • Human computation
  • Interactive machine learning
  • Sentiment analysis
  • User generated content

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

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