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Towards Objective-Dependent Performance Analysis on Online Sentiment Review

  • Doaa Mohey El-Din
  • Mohamed Hamed N. Taha
  • Nour Eldeen M. Khalifa
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 801)

Abstract

This chapter represents a new object dependent for online review evaluation for improving performance by a proposed performance criterion. This criterion can introduce an alternative solution for measuring sentiment accuracy. The problem illustrates in the accuracy comparison measurement between different sentiment techniques and frameworks. Each technique or framework targets one sentiment challenge or more. Another challenge appears in constructing database and its characteristics as memorability. For example, if two sentiment techniques are equal percentage of accuracy, the problem is that meaning they are achieved to the same classification, polarity and score. Is the sentiment challenge accuracy with 10% is bad? So, this study compares between several techniques based on proposed performance assessment. This assessment puts them in the same environment with respect three perspective. It is a new proposed criterion for performance measurement, which includes aggregation of performance measurement types: F-measure and Runtime with respect to speed of run time, memorability, and sentiment analysis challenge type. A comparison between several sentiment techniques is in movie domain in English language. It works on word-level sentiment analysis to measure the proposed performance criteria. It applies two experiments to evaluate the percentage degree of different techniques performance on measuring sentiments.

Keywords

Objective-dependent performance analysis Online sentiment review Sentiment performance criteria 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Doaa Mohey El-Din
    • 1
  • Mohamed Hamed N. Taha
    • 1
  • Nour Eldeen M. Khalifa
    • 1
  1. 1.Faculty of Computers and InformationCairo UniversityGizaEgypt

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