Software

Sentiment Identification by Incorporating Syntax, Semantics and Context Information

Download Now Free registration required

Executive Summary

Understanding the sentiment of sentences allows users to summarize opinions which could help people make informed decisions. All of the state-of-the-art algorithms perform well on individual sentences without considering any context in-formation, but their accuracy is dramatically lower on the document level because they fail to consider context and the syntactic structure of sentences at the same time. This paper proposes a method based on conditional random fields to incorporate sentence structure (syntax and semantics) and context information to identify sentiments of sentences within a document. It also proposes and evaluates two different active learning strategies for labeling sentiment data. The experiments with the proposed approach demonstrate a 5-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods.

  • Format: PDF
  • Size: 458.34 KB