Depression Detection Using Deep Learning and Natural Language Processing Techniques: A Comparative Study

Author:

Mesquita FranciscoORCID,Maurício JoséORCID,Marques GonçaloORCID

Publisher

Springer Nature Switzerland

Reference32 articles.

1. Depression. https://www.who.int/news-room/fact-sheets/detail/depression. Accessed 26 Oct 2022

2. TF-IDF for Document Ranking from scratch in python on real world dataset. https://towardsdatascience.com/tf-idf-for-document-ranking-from-scratch-in-python-on-real-world-dataset-796d339a4089. Accessed 09 Jan 2023

3. Al-Garaady, J., Mahyoob, M.: Public sentiment analysis in social media on the SARS-CoV-2 vaccination using VADER lexicon polarity (2022)

4. Almeida, F., Xexéo, G.: Word embeddings: a survey (2019). https://doi.org/10.48550/arXiv.1901.09069

5. Alsagri, H.S., Ykhlef, M.: Machine learning-based approach for depression detection in twitter using content and activity features. IEICE Trans. Inf. Syst. E103.D(8), 1825–1832 (2020). https://doi.org/10.1587/transinf.2020EDP7023

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