Performance of Content-Based Features to Detect Depression Tendencies in Different Text Lengths
Author:
Affiliation:
1. Universiti Teknikal Malaysia Melaka,Fakulti Teknologi Maklumat dan Komunikasi,Durian Tunggal,Melaka,Malaysia,76100
2. Mastery Academy,Shah Alam,Selangor
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9936688/9936734/09936811.pdf?arnumber=9936811
Reference25 articles.
1. Psychological Analysis for Depression Detection from Social Networking Sites
2. Depression Detection in Single Tweets Using Content-Based Features;zulkarnain;Proceedings of the 3rd International Conference on Intelligent and Interactive Computing 2021,2021
3. Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals
4. Detecting depression and mental illness on social media: an integrative review
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1. A Hybrid Approach for Depression Classification Using BERT and SVM;Lecture Notes in Networks and Systems;2024
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