[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 …
Understanding emotions in text using deep learning and big data
A Chatterjee, U Gupta, MK Chinnakotla… - Computers in Human …, 2019 - Elsevier
Abstract Big Data and Deep Learning algorithms combined with enormous computing power
have paved ways for significant technological advancements. Technology is evolving to …
have paved ways for significant technological advancements. Technology is evolving to …
A sentiment-and-semantics-based approach for emotion detection in textual conversations
U Gupta, A Chatterjee, R Srikanth… - arXiv preprint arXiv …, 2017 - arxiv.org
Emotions are physiological states generated in humans in reaction to internal or external
events. They are complex and studied across numerous fields including computer science …
events. They are complex and studied across numerous fields including computer science …
Few-shot emotion recognition in conversation with sequential prototypical networks
Detecting emotions in a conversational context benefits several industrial cases such as
customer service, user appraisal from speech recognition, and so on. However, in most …
customer service, user appraisal from speech recognition, and so on. However, in most …
Deep learning-based social media mining for user experience analysis: A case study of smart home products
J Wang, YL Liu - Technology in Society, 2023 - Elsevier
Understanding and enhancing user experience (UX) is crucial for new product innovation.
Abundant user-generated content (UGC) from social media contains information about …
Abundant user-generated content (UGC) from social media contains information about …
Deep rolling: A novel emotion prediction model for a multi-participant communication context
Nowadays, the amount of user-generated contents (UGCs) or texts has surged
exponentially. Therefore, recognizing emotions from these texts can bring about lots of …
exponentially. Therefore, recognizing emotions from these texts can bring about lots of …
Deep learning neural networks for emotion classification from text: enhanced leaky rectified linear unit activation and weighted loss
H Yang, A Alsadoon, PWC Prasad, T Al-Dala'in… - Multimedia Tools and …, 2022 - Springer
Accurate emotion classification for online reviews is vital for business organizations to gain
deeper insights into markets. Although deep learning has been successfully implemented in …
deeper insights into markets. Although deep learning has been successfully implemented in …
NELEC at SemEval-2019 task 3: think twice before going deep
P Agrawal, A Suri - arXiv preprint arXiv:1904.03223, 2019 - arxiv.org
Existing Machine Learning techniques yield close to human performance on text-based
classification tasks. However, the presence of multi-modal noise in chat data such as …
classification tasks. However, the presence of multi-modal noise in chat data such as …
Emotion detection in text: focusing on latent representation
In recent years, emotion detection in text has become more popular due to its vast potential
applications in marketing, political science, psychology, human-computer interaction …
applications in marketing, political science, psychology, human-computer interaction …
A survey of emotion analysis in text based on deep learning
L Cao, S Peng, P Yin, Y Zhou… - 2020 IEEE 8th …, 2020 - ieeexplore.ieee.org
With the rapid development of mobile Internet, and the popularization of e-commerce and
social networks, people have changed from the simple users of network information to the …
social networks, people have changed from the simple users of network information to the …