Emotional sentiment analysis of social media content for mental health safety
Dados Bibliográficos
| ID | 4614409 |
|---|---|
| Autores | Ferdaous Benrouba (Badji Mokhtar University, autor correspondente), Rachid Boudour (Badji Mokhtar University) |
| Ano | 2023 |
| Volume | 13 |
| Fascículo | 1 |
| Data de publicação | 2023-01-02 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Social Network Analysis and Mining (JOURNAL) |
| Identificadores do periódico | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Editora | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-022-01000-9 |
| OpenAlex | W4313392084 |
| Idioma | EN |
| Citações recebidas | 8 |
| Referências citadas | 31 |
Anger · Content analysis · Data science · Disgust · Mood · Sadness · Sentiment analysis · Social media · World Wide Web · Computer Science · Mental Health via Writing · Psychology · Sentiment Analysis and Opinion Mining · Social Psychology · Spam and Phishing Detection · Artificial Intelligence
The Linguistic Landscape of “Controversial”
Sentiment Analysis on Twitter
The ethical aspects of integrating sentiment and emotion analysis in chatbots for depression intervention
‘Seals’, ‘bitches’, ‘vixens’, and other zoomorphic insults
Communicating Global Public Health Emergency
LexiSNTAGMM
AI recommendations’ impact on individual and social practices of Generation Z on social media
Identifying discernible indications of psychological well-being using ML
| Obras citantes distintas | 8 |
|---|---|
| Citações por ano | 2,67 |
| Intervalo de citações | 2023 - 2026 (4) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 7 |