Sentiment analysis meets semantic analysis: Constructing insight knowledge bases

Zirun Qi, Veda C. Storey, Wael Jabr

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

Numerous Web 2.0 applications collect user opinions, and other user-generated content in the form of product reviews, discussion boards, and blogs, which are often captured as unstructured data. Text mining techniques are important for analyzing users' opinions (sentiment analysis) and identifying topics of interest (semantic analysis). However, little work has been carried out that combines semantics with user' sentiments. This research proposes a Sentiment-Semantic Framework that incorporates results from both semantic and sentiment analysis to construct a knowledge base of insights gained from integrating the information extracted from each type of analysis. To evaluate the framework, a prototype is developed and applied to two different domains (e-commerce and politics) and the resulting insight knowledge bases constructed.

Original languageEnglish (US)
StatePublished - 2015
Event2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015 - Fort Worth, United States
Duration: Dec 13 2015Dec 16 2015

Other

Other2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015
CountryUnited States
CityFort Worth
Period12/13/1512/16/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences
  • Applied Mathematics

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