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Improvement on Emotional Variance Analysis Technique (EVA) for Sentiment Analysis in Healthcare Service Delivery

by Virtue Ene Agada, Adebola K. Ojo
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 44
Year of Publication: 2024
Authors: Virtue Ene Agada, Adebola K. Ojo
10.5120/ijais2024451970

Virtue Ene Agada, Adebola K. Ojo . Improvement on Emotional Variance Analysis Technique (EVA) for Sentiment Analysis in Healthcare Service Delivery. International Journal of Applied Information Systems. 12, 44 ( May 2024), 10-16. DOI=10.5120/ijais2024451970

@article{ 10.5120/ijais2024451970,
author = { Virtue Ene Agada, Adebola K. Ojo },
title = { Improvement on Emotional Variance Analysis Technique (EVA) for Sentiment Analysis in Healthcare Service Delivery },
journal = { International Journal of Applied Information Systems },
issue_date = { May 2024 },
volume = { 12 },
number = { 44 },
month = { May },
year = { 2024 },
issn = { 2249-0868 },
pages = { 10-16 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number44/improvement-on-emotional-variance-analysis-technique-eva-for-sentiment-analysis-in-healthcare-service-delivery/ },
doi = { 10.5120/ijais2024451970 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-05-30T21:54:12+05:30
%A Virtue Ene Agada
%A Adebola K. Ojo
%T Improvement on Emotional Variance Analysis Technique (EVA) for Sentiment Analysis in Healthcare Service Delivery
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 44
%P 10-16
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research introduces an innovative approach to improving sentiment analysis in healthcare service delivery by integrating Emotion and Affect Recognition (EAR) techniques into Emotional Variance Analysis (EVA). Leveraging logistic regression, the modifications, including adjusting confidence thresholds and utilizing the Rectified Linear Unit (ReLU) function, aim to address high polarity and enable real-time analysis. The methodology outlines a systematic process for EAR integration, offering practical insights for healthcare practitioners. In this study, additional datasets, including the Healthcare Patient Satisfaction Data Collection, the 9 Popular Patient Portal App Reviews for November 2023, and the HCAHPS Hospital Ratings Survey, are incorporated to enhance the robustness and reliability of the approach. The results across three healthcare centers demonstrate the effectiveness of this augmented approach, with comparisons against existing models using performance metrics. While showcasing promising potential, further research is needed to explore scalability and generalizability.

References
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Index Terms

Computer Science
Information Sciences
Data Mining
Sentiment Analysis
Machine Learning
Healthcare Informatics
Algorithms
Natural Language Processing (NLP)
Emotion and Affect Recognition

Keywords

Emotional Variance Analysis (EVA) Healthcare Service Delivery Emotion Recognition Affect Recognition Logistic Regression Feature Scaling Real-Time Analysis Healthcare Reviews Patient Satisfaction Data Integration Text Mining

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