Emotional sentiment analysis of social media content for mental health safety
Bibliographic Data
| ID | 4614409 |
|---|---|
| Authors | Ferdaous Benrouba (Badji Mokhtar University, corresponding author), Rachid Boudour (Badji Mokhtar University) |
| Year | 2023 |
| Volume | 13 |
| Issue | 1 |
| Publication date | 2023-01-02 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-022-01000-9 |
| OpenAlex | W4313392084 |
| Language | EN |
| Citations received | 8 |
| References cited | 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
| Unique citing works | 8 |
|---|---|
| Citations per year | 2,67 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |