# Deep Learning-Based Detection of Depression and Suicidal Tendencies in Social Media Data with Feature Selection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-based-detection-of-depression-and-suicidal-tendencies-in-social/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ismail BAYDİLİ,Burak Taşçı,Gülay Taşçı |
| Citations | 37 |
| DOI | 10.3390/bs15030352 |
| Fields | Computer Science,Psychology |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2076-328X/15/3/352/pdf?version=1741796953 |
| OpenAlex ID | https://openalex.org/W4408414579 |
| PMID | 40150247 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Gülay Taşçı](https://scholariq.org/researchers/gulay-tasc/)

## Paper journal

- [Behavioral Sciences](https://scholariq.org/journals/behavioral-sciences/)

## Paper primary topic

- [Mental Health via Writing](https://scholariq.org/topics/mental-health-via-writing/)

## Paper topics

- [Mental Health via Writing](https://scholariq.org/topics/mental-health-via-writing/)
- [Digital Mental Health Interventions](https://scholariq.org/topics/digital-mental-health-interventions/)
- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.