[HTML][HTML] A survey on deep learning for textual emotion analysis in social networks
S Peng, L Cao, Y Zhou, Z Ouyang, A Yang, X Li… - Digital Communications …, 2022 - Elsevier
Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
A survey of textual emotion recognition and its challenges
Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …
processing, textual emotion recognition (TER) has become an important topic due to its …
A survey of state-of-the-art approaches for emotion recognition in text
N Alswaidan, MEB Menai - Knowledge and Information Systems, 2020 - Springer
Emotion recognition in text is an important natural language processing (NLP) task whose
solution can benefit several applications in different fields, including data mining, e-learning …
solution can benefit several applications in different fields, including data mining, e-learning …
AI-based conversational agents: a scoping review from technologies to future directions
Artificial intelligence is changing the world, especially the interaction between machines and
humans. Learning and interpreting natural languages and responding have paved the way …
humans. Learning and interpreting natural languages and responding have paved the way …
AI based emotion detection for textual big data: Techniques and contribution
Online Social Media (OSM) like Facebook and Twitter has emerged as a powerful tool to
express via text people's opinions and feelings about the current surrounding events …
express via text people's opinions and feelings about the current surrounding events …
A systematic review of applications of natural language processing and future challenges with special emphasis in text-based emotion detection
Artificial Intelligence (AI) has been used for processing data to make decisions, Interact with
humans, and understand their feelings and emotions. With the advent of the Internet, people …
humans, and understand their feelings and emotions. With the advent of the Internet, people …
[PDF][PDF] BERT-CNN: A Deep Learning Model for Detecting Emotions from Text.
Due to the widespread usage of social media in our recent daily lifestyles, sentiment
analysis becomes an important field in pattern recognition and Natural Language …
analysis becomes an important field in pattern recognition and Natural Language …
A review on emotion detection by using deep learning techniques
Along with the growth of Internet with its numerous potential applications and diverse fields,
artificial intelligence (AI) and sentiment analysis (SA) have become significant and popular …
artificial intelligence (AI) and sentiment analysis (SA) have become significant and popular …
Deep transfer learning baselines for sentiment analysis in Russian
S Smetanin, M Komarov - Information Processing & Management, 2021 - Elsevier
Recently, transfer learning from pre-trained language models has proven to be effective in a
variety of natural language processing tasks, including sentiment analysis. This paper aims …
variety of natural language processing tasks, including sentiment analysis. This paper aims …
Textual emotion classification using MPNet and cascading broad learning
As one of the most important tasks of natural language processing, textual emotion
classification (TEC) aims to recognize and detect all emotions contained in texts. However …
classification (TEC) aims to recognize and detect all emotions contained in texts. However …