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An explainable ensemble model for revealing the level of depression in social media by considering personality traits and sentiment polarity pattern

Bibliographic Data

ID22156838
AuthorsGede Aditra Pradnyana (0000-0002-7821-8566, Sepuluh Nopember Institute of Technology), Wiwik Anggraeni (0000-0003-3010-3062, Sepuluh Nopember Institute of Technology), Eko Mulyanto Yuniarno (0000-0003-1243-3025, Sepuluh Nopember Institute of Technology), Mauridhi Hery Purnomo (0000-0002-6221-7382, Sepuluh Nopember Institute of Technology, corresponding author)
Year2025
Volume46
Pages100307
Publication date2025-05-01
Open AccessYes
TypeARTICLE
VenueOnline Social Networks and Media (JOURNAL)
Journal identifiersISSN: 2468-6964 • E-ISSN: 2468-6964
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.osnem.2025.100307
OpenAlexW4408249562
LanguageEN
Citations received2
References cited34

Big Five personality traits · Biology · Cognitive psychology · Data science · Economics · Personality · Sentiment analysis · Social media · World Wide Web · Complex Network Analysis Techniques · Computer Science · Mental Health via Writing · Psychology · Sentiment Analysis and Opinion Mining · Social Psychology · Artificial Intelligence

  • Online expressions, offline struggles

    Open Access•Mario Ezra Aragón, Adrián Pastor López-Monroy et al.•Online Social Networks and Media•2025

  • How does depression talk on social media? Modeling depression language with relevance-based statistical language models

    Open Access•Eliseo Bao, Anxo Perez et al.•Online Social Networks and Media•2025

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  • Multitask learning for recognizing stress and depression in social media

    Open Access•Loukas Ilias, Dimitris Askounis•Online Social Networks and Media•2023

  • Ensemble Hybrid Learning Methods for Automated Depression Detection

    Open Access•Luna Ansari, Shaoxiong Ji et al.•IEEE Transactions on Computational…•2023

  • Depression Screening in Humans With AI and Deep Learning Techniques

    Open Access•Mudasir Ahmad Wani, Mohammed El Affendi et al.•IEEE Transactions on Computational…•2023

  • What Does Your Bio Say? Inferring Twitter Users’ Depression Status From Multimodal Profile Information Using Deep Learning

    Open Access•Soumitra Ghosh, Asif Ekbal et al.•IEEE Transactions on Computational…•2022

  • Depression Intensity Estimation via Social Media

    Open Access•Shreya Ghosh, Tarique Anwar•IEEE Transactions on Computational…•2021

  • The effects of personality and social media experiences on mental health

    Open Access•Hermann Astleitner, Amrit Bains et al.•Computers in Human Behavior•2023

  • “Are we tweeting our real selves?” personality prediction of Indian Twitter users using deep learning ensemble model

    Open Access•Rhea Mahajan, Remia Mahajan et al.•Computers in Human Behavior•2022

  • Longitudinal associations among neuroticism, depression, and cyberbullying in early adolescents

    Open Access•Danfeng Zhang, E Scott Huebner et al.•Computers in Human Behavior•2020

  • Dress in Spartan Society

    Open Access•Ephraim David, Tianlin Zhang et al.•Post-Medieval Archaeology•2003

Citations per year2
Citation span2025 - 2025 (1)
Highly citedNo

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