Unveiling the Emotions: A Sentiment Analysis of Amazon Customer Feedback
- Title
- Unveiling the Emotions: A Sentiment Analysis of Amazon Customer Feedback
- Creator
- Muthu Ruben V.; VijayaKumar R.; Sateesh Kumar T.K.
- Description
- This study explores sentiment analysis in the context of diverse regions and contemporary customer feedback, aiming to address research questions related to consolidation based on polarity scores and sentiments. The research utilizes multinomial regression for a comprehensive analysis of customer feedback worldwide. The investigation incorporates confusion matrices, statistics, and class-specific metrics to evaluate the models performance. Results indicate a highly accurate model with perfect sensitivity, specificity, and overall accuracy. The analysis further includes a breakdown of key metrics such as accuracy, confidence intervals, no information rate, p-value, kappa, and prevalence, emphasizing the models robustness. In conclusion, the multinomial logistic regression model demonstrates exceptional performance in predicting sentiment across diverse classes, highlighting its effectiveness in sentiment analysis on a global scale. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
- Source
- Studies in Systems, Decision and Control, Vol-536, pp. 403-410.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Amazon customer feedback; Confusion matrix; Machine learning; Sentiment analysis; Word cloud
- Coverage
- Muthu Ruben V., School of Law, Christ University, Bangalore, India; VijayaKumar R., Kristu Jayanti College (Autonomous), Bangalore, India; Sateesh Kumar T.K., Kristu Jayanti College (Autonomous), Bangalore, India
- Rights
- Restricted Access
- Relation
- ISSN: 21984182
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Muthu Ruben V.; VijayaKumar R.; Sateesh Kumar T.K., “Unveiling the Emotions: A Sentiment Analysis of Amazon Customer Feedback,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 22, 2025, https://archives.christuniversity.in/items/show/17954.