{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T13:51:32Z","timestamp":1783000292552,"version":"3.54.5"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soc. Netw. Anal. Min."],"DOI":"10.1007\/s13278-024-01206-z","type":"journal-article","created":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T16:02:58Z","timestamp":1708704178000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Detection of depressive comments on social media using RNN, LSTM, and random forest: comparison and optimization"],"prefix":"10.1007","volume":"14","author":[{"given":"Manuel","family":"Kanahuati-Ceballos","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonardo J.","family":"Valdivia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,23]]},"reference":[{"key":"1206_CR1","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/s11126-017-9535-6","volume":"89","author":"C Berryman","year":"2018","unstructured":"Berryman C, Ferguson CJ, Negy C (2018) Social media use and mental health among young adults. Psychiatr Q 89:307\u2013314","journal-title":"Psychiatr Q"},{"issue":"5","key":"1206_CR2","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1080\/03007995.2022.2038487","volume":"38","author":"S Bhadra","year":"2022","unstructured":"Bhadra S, Kumar CJ (2022) An insight into diagnosis of depression using machine learning techniques: a systematic review. Curr Med Res Opin 38(5):749\u2013771. https:\/\/doi.org\/10.1080\/03007995.2022.2038487","journal-title":"Curr Med Res Opin"},{"key":"1206_CR3","doi-asserted-by":"publisher","DOI":"10.1080\/10255842.2023.2181660","author":"S Bhadra","year":"2023","unstructured":"Bhadra S, Kumar CJ (2023) Enhancing the efficacy of depression detection system using optimal feature selection from EHR. Comput Methods Biomech Biomed Engin. https:\/\/doi.org\/10.1080\/10255842.2023.2181660","journal-title":"Comput Methods Biomech Biomed Engin"},{"key":"1206_CR4","doi-asserted-by":"publisher","first-page":"106160","DOI":"10.1016\/j.chb.2019.106160","volume":"104","author":"SM Coyne","year":"2020","unstructured":"Coyne SM, Rogers AA, Zurcher JD, Stockdale L, Booth M (2020) Does time spent using social media impact mental health?: An eight year longitudinal study. Comput Hum Behav 104:106160","journal-title":"Comput Hum Behav"},{"key":"1206_CR5","unstructured":"CS 230 - Recurrent Neural Networks Cheatsheet. (n.d.) https:\/\/stanford.edu\/~shervine\/teaching\/cs-230\/cheatsheet-recurrent-neural-networks"},{"key":"1206_CR6","unstructured":"Depression: Reddit Dataset (Cleaned). (2022) Kaggle. https:\/\/www.kaggle.com\/datasets\/infamouscoder\/depression-reddit-cleaned"},{"key":"1206_CR7","unstructured":"Depression: Twitter Dataset + Feature Extraction. (2022) Kaggle. https:\/\/www.kaggle.com\/datasets\/infamouscoder\/mental-health-social-media"},{"key":"1206_CR8","first-page":"503","volume-title":"Deep learning: RNNs and LSTM","author":"RS DiPietro","year":"2019","unstructured":"DiPietro RS, Hager GD (2019) Deep learning: RNNs and LSTM. Elsevier eBooks, Amsterdam, pp 503\u2013519"},{"key":"1206_CR9","unstructured":"Frazier PI (2018) A tutorial on Bayesian optimization. arXiv.org. https:\/\/arxiv.org\/abs\/1807.02811"},{"key":"1206_CR10","unstructured":"G\u00e9rard B, G\u00e9rard B, Erwan S (2015) A random forest guided tour. arXiv: Statistics Theory"},{"issue":"6","key":"1206_CR11","first-page":"512","volume":"14","author":"CJ Kumar","year":"2022","unstructured":"Kumar CJ, Das PR, Hazarika A (2022) Autism spectrum disorder diagnosis and machine learning: a review. Int J Med Eng Inform 14(6):512\u2013527","journal-title":"Int J Med Eng Inform"},{"key":"1206_CR12","unstructured":"Linguistic Features \u00b7 spaCy Usage Documentation. (n.d.) Linguistic Features. https:\/\/spacy.io\/usage\/linguistic-features#lemmatization"},{"key":"1206_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jadr.2022.100385","author":"AR Merrill","year":"2022","unstructured":"Merrill AR, Cao C, Primack AB (2022) Associations between social media use, personality structure, and development of depression. J Affect Disord Rep. https:\/\/doi.org\/10.1016\/j.jadr.2022.100385","journal-title":"J Affect Disord Rep"},{"key":"1206_CR14","unstructured":"Nadeem, M. (2016) Identifying depression on Twitter.\u00a0arXiv preprint arXiv:1607.07384"},{"key":"1206_CR15","unstructured":"NLTK: Natural Language Toolkit. (n.d.) https:\/\/www.nltk.org\/"},{"issue":"5","key":"1206_CR16","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1093\/heapro\/day056","volume":"34","author":"M O\u2019Reilly","year":"2019","unstructured":"O\u2019Reilly M, Dogra N, Hughes J, Reilly P, George R, Whiteman N (2019) Potential of social media in promoting mental health in adolescents. Health Promot Int 34(5):981\u2013991","journal-title":"Health Promot Int"},{"key":"1206_CR17","unstructured":"Optuna - A hyperparameter optimization framework. (n.d.) Optuna. https:\/\/optuna.org\/#key_features"},{"issue":"8","key":"1206_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1142\/S0218213022500403","volume":"31","author":"M Sharma","year":"2022","unstructured":"Sharma M, Kumar CJ (2022) Improving rice disease diagnosis using ensemble Transfer learning techniques. Int J Artif Intell Tools 31(8):1\u201315","journal-title":"Int J Artif Intell Tools"},{"issue":"4","key":"1206_CR19","first-page":"321","volume":"7","author":"M Sharma","year":"2021","unstructured":"Sharma M, Kumar CJ, Deka A (2021) Land cover classification: a comparative analysis of clustering techniques using Sentinel-2 data. Int J Sustain Agric Manag Informat 7(4):321\u2013342","journal-title":"Int J Sustain Agric Manag Informat"},{"issue":"1","key":"1206_CR20","doi-asserted-by":"publisher","first-page":"20220689","DOI":"10.1515\/biol-2022-0689","volume":"18","author":"M Sharma","year":"2023","unstructured":"Sharma M, Kumar CJ, Talukdar J, Singh TP, Dhiman G, Sharma A (2023) Identification of rice leaf diseases and deficiency disorders using a novel DeepBatch technique. Open Life Sci 18(1):20220689. https:\/\/doi.org\/10.1515\/biol-2022-0689","journal-title":"Open Life Sci"},{"issue":"1","key":"1206_CR21","doi-asserted-by":"publisher","first-page":"24","DOI":"10.36548\/JTCSST.2021.1.003","volume":"3","author":"DS Smys","year":"2021","unstructured":"Smys DS, Raj DJS (2021) Analysis of deep learning techniques for early detection of depression on social media network-a comparative study. J Trends Comput Sci Smart Technol 3(1):24\u201339. https:\/\/doi.org\/10.36548\/JTCSST.2021.1.003","journal-title":"J Trends Comput Sci Smart Technol"},{"key":"1206_CR22","unstructured":"Text Classification: What it is And Why it Matters. (n.d.) MonkeyLearn. https:\/\/monkeylearn.com\/text-classification\/"},{"issue":"8","key":"1206_CR23","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/J.PATREC.2005.10.010","volume":"27","author":"F Tom","year":"2006","unstructured":"Tom F (2006) An introduction to ROC analysis. Pattern Recogn Lett 27(8):861\u2013874. https:\/\/doi.org\/10.1016\/J.PATREC.2005.10.010","journal-title":"Pattern Recogn Lett"},{"key":"1206_CR24","unstructured":"Verma Y (2023) A complete understanding of dense layers in neural networks. Analytics India Magazine. https:\/\/analyticsindiamag.com\/a-complete-understanding-of-dense-layers-in-neural-networks\/"},{"key":"1206_CR25","unstructured":"What is Overfitting? - Overfitting in Machine Learning Explained - AWS. (n.d.) Amazon Web Services, Inc. https:\/\/aws.amazon.com\/what-is\/overfitting\/?nc1=h_ls"},{"issue":"3","key":"1206_CR26","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1017\/S0033291714001640","volume":"45","author":"S Wilson","year":"2015","unstructured":"Wilson S, Hicks BM, Foster KT, McGue M, Iacono WG (2015) Age of onset and course of major depressive disorder: associations with psychosocial functioning outcomes in adulthood. Psychol Med 45(3):505\u2013514. https:\/\/doi.org\/10.1017\/S0033291714001640","journal-title":"Psychol Med"},{"key":"1206_CR27","unstructured":"World Health Organization (2020) Depression [Fact sheet]. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/depression"},{"key":"1206_CR28","unstructured":"World Health Organization: WHO & World Health Organization: WHO. (2023) Depressive disorder (depression). www.who.int. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/depression"},{"issue":"1\u20134","key":"1206_CR29","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s13042-010-0001-0","volume":"1","author":"Y Zhang","year":"2010","unstructured":"Zhang Y, Jin R, Zhou Z (2010) Understanding bag-of-words model: a statistical framework. Int J Mach Learn Cybern 1(1\u20134):43\u201352. https:\/\/doi.org\/10.1007\/s13042-010-0001-0","journal-title":"Int J Mach Learn Cybern"},{"key":"1206_CR30","unstructured":"Zvornicanin E, Zvornicanin E (2023) What are embedding layers in neural networks? | Baeldung on Computer Science. Baeldung on Computer Science. https:\/\/www.baeldung.com\/cs\/neural-nets-embedding-layers"}],"container-title":["Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-024-01206-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13278-024-01206-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-024-01206-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T14:13:34Z","timestamp":1740492814000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13278-024-01206-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,23]]},"references-count":30,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["1206"],"URL":"https:\/\/doi.org\/10.1007\/s13278-024-01206-z","relation":{},"ISSN":["1869-5469"],"issn-type":[{"value":"1869-5469","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,23]]},"assertion":[{"value":"1 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 January 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 February 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"44"}}