p-Norm Broad Learning for Negative Emotion Classification in Social Networks
Negative emotion classification refers to the automatic classification of negative emotion of texts in social networks. Most existing methods are based on deep learning models, facing challenges such as complex structures and too many hyperparameters. To meet these challenges, in this paper, we prop...
Saved in:
Main Authors: | Guanghao Chen, Sancheng Peng, Rong Zeng, Zhongwang Hu, Lihong Cao, Yongmei Zhou, Zhouhao Ouyang, Xiangyu Nie |
---|---|
Format: | Article |
Language: | English |
Published: |
Tsinghua University Press
2022-09-01
|
Series: | Big Data Mining and Analytics |
Subjects: | |
Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2022.9020008 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Negative frequencies and negative norms in analogue Hawking radiation systems
by: Aguero-Santacruz, Raul, et al.
Published: (2024-04-01) -
The relationship between smartphone addiction and sleep disorder among college students: negative emotions as a mediator and gender as a moderator
by: Siyi Li, et al.
Published: (2025-02-01) -
Electroacupuncture Alleviates Neuropathic Pain and Negative Emotion in Mice by Regulating Gut Microbiota
by: Feng C, et al.
Published: (2025-01-01) -
The Role of Different Emotional States of Customers on Food Preferences
by: Mahmood Ghanbari, et al.
Published: (2024-06-01) -
Broad spectrum micronutrients: a potential key player to address emotional dysregulation
by: Amelia Villagomez, et al.
Published: (2023-12-01)