Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions-Reference-Cited by-同舟云学术

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Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions

Published:2022-12-16 Issue: Volume: Page:1-26
ISSN:0144-929X
Container-title:Behaviour & Information Technology
language:en
Short-container-title:Behaviour & Information Technology

Author:

Alslaity Alaa¹^ORCID,Orji Rita¹^ORCID

Affiliation:

1. Faculty of Computer Science, Dalhousie University, Halifax, Canada

Funder

Natural

Sciences

and

Engineering

Research

Council

of

Canada

Publisher

Informa UK Limited

Subject

Human-Computer Interaction,General Social Sciences,Arts and Humanities (miscellaneous),Developmental and Educational Psychology

Link

https://www.tandfonline.com/doi/pdf/10.1080/0144929X.2022.2156387

Reference107 articles.

1. Predicting the sentiment of SaaS online reviews using supervised machine learning techniques

2. Emotions from text

3. Users’ Responsiveness to Persuasive Techniques in Recommender Systems

4. A novel sentiment analysis of social networks using supervised learning

5. A hybrid approach to the sentiment analysis problem at the sentence level

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1. Automatic Recognition of Multiple Emotional Classes from EEG Signals through the Use of Graph Theory and Convolutional Neural Networks;Sensors;2024-09-10

2. Comprehensive review and comparative analysis of transformer models in sentiment analysis;Knowledge and Information Systems;2024-09-06

3. An Enhanced IDBO-CNN-BiLSTM Model for Sentiment Analysis of Natural Disaster Tweets;Biomimetics;2024-09-04

4. Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data;Journal of Sensor and Actuator Networks;2024-08-03

5. Enhanced multimodal emotion recognition in healthcare analytics: A deep learning based model-level fusion approach;Biomedical Signal Processing and Control;2024-08

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