A hybrid approach for the detection and monitoring of people having personality disorders on social networks
Bibliographic Data
| ID | 4694069 |
|---|---|
| Authors | Mourad Ellouze (0000-0001-7831-5318, University of Sfax, corresponding author), Lamia Hadrich Belguith (0000-0002-5063-9246, University of Sfax) |
| Year | 2022 |
| Volume | 12 |
| Issue | 1 |
| Pages | 67-67 |
| Publication date | 2022-12-01 |
| 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/s13278-022-00884-x |
| PMID | 35789887 |
| OpenAlex | W4283592650 |
| Language | EN |
| Citations received | 4 |
| References cited | 45 |
Machine learning · Natural language processing · Personality · Support vector machine · Authorship Attribution and Profiling · Computer Science · Machine Learning in Healthcare · Mathematics · Mental Health via Writing · Psychology · Social Psychology · Artificial Intelligence
Management of psychological emergency cases on social media
Semantic analysis based on ontology and deep learning for a chatbot to assist persons with personality disorders on Twitter
Advancing aspect-based sentiment analysis with a novel architecture combining deep learning models CNN and bi-RNN with the machine learning model SVM
Text classification models for personality disorders identification
| Citations per year | 1.33 |
|---|---|
| Citation span | 2023 - 2025 (3) |
| Highly cited | No |