{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:22:35Z","timestamp":1771701755575,"version":"3.50.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T00:00:00Z","timestamp":1701043200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T00:00:00Z","timestamp":1701043200000},"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":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17395-2","type":"journal-article","created":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T03:01:42Z","timestamp":1701054102000},"page":"53923-53948","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Stacked ensemble model for analyzing mental health disorder from social media data"],"prefix":"10.1007","volume":"83","author":[{"given":"Divya","family":"Agarwal","sequence":"first","affiliation":[]},{"given":"Vijay","family":"Singh","sequence":"additional","affiliation":[]},{"given":"Ashwini Kumar","family":"Singh","sequence":"additional","affiliation":[]},{"given":"Parul","family":"Madan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,27]]},"reference":[{"key":"17395_CR1","doi-asserted-by":"crossref","unstructured":"Cleofas JV (2022)\u00a0Social media disorder during community quarantine: a\u00a0mixed methods study among rural young\u00a0college students during the COVID-19 pandemic. Arch Psychiatr Nurs 40:97\u2013105","DOI":"10.1016\/j.apnu.2022.06.003"},{"key":"17395_CR2","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.apnu.2022.03.007","volume":"40","author":"L Liang","year":"2022","unstructured":"Liang L, Li C, Meng C, Guo X, Lv J, Fei J, Mei S (2022) Psychological distress and internet addiction following the COVID-19 outbreak: Fear of missing out and boredom proneness as mediators. Arch Psychiatr Nurs 40:8\u201314","journal-title":"Arch Psychiatr Nurs"},{"key":"17395_CR3","doi-asserted-by":"crossref","unstructured":"Precht L-M, Stirnberg J, Margraf J, Brailovskaia J (2022) Can physical activity foster mental health by preventing addictive social media use? \u2013 A longitudinal investigation during the COVID-19 pandemic in Germany. J Affect Disord Rep 8","DOI":"10.1016\/j.jadr.2022.100316"},{"key":"17395_CR4","doi-asserted-by":"crossref","unstructured":"Boniel-Nissim M et al (2022) International perspectives on social media use among adolescents: Implications for mental and social well-being and substance use. Comput Hum Behav 129:107144","DOI":"10.1016\/j.chb.2021.107144"},{"key":"17395_CR5","doi-asserted-by":"crossref","unstructured":"St\u0103nculescu E, Griffiths MD (2022) Social media addiction profiles and their antecedents using latent profile analysis: the contribution of social anxiety, gender, and age. Telematics Inform 74:101879","DOI":"10.1016\/j.tele.2022.101879"},{"key":"17395_CR6","doi-asserted-by":"crossref","unstructured":"El Abiddine FZ et al (2022) Mediated effects of insomnia in the association between problematic social media use and subjective well-being among university students during COVID-19 pandemic. Sleep Epidemiology 2:100030","DOI":"10.1016\/j.sleepe.2022.100030"},{"key":"17395_CR7","doi-asserted-by":"crossref","unstructured":"Hattingh M, Dhir A, Ractham P, Ferraris A, Yahiaoui D (2022) Factors mediating social media-induced fear of missing out (FoMO) and social media fatigue: a comparative study among Instagram and Snapchat users. Technol Forecast Soc Chang 185","DOI":"10.1016\/j.techfore.2022.122099"},{"key":"17395_CR8","doi-asserted-by":"crossref","unstructured":"Roberts SR et al (2022) Incorporating social media and muscular ideal internalization into the tripartite influence model of body image: towards a modern understanding of adolescent girls\u2019 body dissatisfaction. Body Image 41:239\u2013247","DOI":"10.1016\/j.bodyim.2022.03.002"},{"key":"17395_CR9","doi-asserted-by":"crossref","unstructured":"Stieger S et al (2022) Engagement with social media content results in lower appearance satisfaction: an experience sampling study using a wrist-worn wearable and a physical analogue scale. Body Image 43:232\u2013243","DOI":"10.1016\/j.bodyim.2022.09.009"},{"key":"17395_CR10","doi-asserted-by":"crossref","unstructured":"Zhao L (2021) The impact of social media use types and social media addiction on subjective well-being of college students: a comparative analysis of addicted and non-addicted students. Comput Human Behav Reports 4:100122","DOI":"10.1016\/j.chbr.2021.100122"},{"key":"17395_CR11","doi-asserted-by":"crossref","unstructured":"Wartberg L, Thomasius R, Paschke K (2021) The relevance of emotion regulation, procrastination, and perceived stress for problematic social media use in a representative sample of children and adolescents. Comput Hum Behav 121:106788","DOI":"10.1016\/j.chb.2021.106788"},{"key":"17395_CR12","doi-asserted-by":"crossref","unstructured":"Lee DS, Way BM (2021) Social media use and systemic inflammation: the moderating role of self-esteem. Brain Behav Immun Health 16:100300","DOI":"10.1016\/j.bbih.2021.100300"},{"key":"17395_CR13","doi-asserted-by":"publisher","first-page":"100429","DOI":"10.1016\/j.mhpa.2021.100429","volume":"21","author":"C Wheatley","year":"2021","unstructured":"Wheatley C, Glogowska M, Stathi A, Sexton C, Johansen-Berg H, Mackay C (2021) Exploring the public health potential of RED January, a social media campaign supporting physical activity in the community for mental health: A qualitative study. Mental Health Phys Act 21:100429","journal-title":"Mental Health Phys Act"},{"key":"17395_CR14","doi-asserted-by":"publisher","first-page":"152197","DOI":"10.1016\/j.comppsych.2020.152197","volume":"103","author":"C Sanchez","year":"2020","unstructured":"Sanchez C, Grzenda A, Varias A, Widge AS, Carpenter LL, McDonald WM, Nemeroff CB, Kalin NH, Martin G, Tohen M, Filippou-Frye M, Ramsey D, Linos E, Mangurian C, Rodriguez CI (2020) Social media recruitment for mental health research: a systematic review. Compr Psychiatr 103:152197","journal-title":"Compr Psychiatr"},{"key":"17395_CR15","doi-asserted-by":"publisher","first-page":"106524","DOI":"10.1016\/j.chb.2020.106524","volume":"114","author":"B Zhong","year":"2020","unstructured":"Zhong B, Huang Y, Liu Q (2020) Mental health toll from the coronavirus: Social media usage reveals Wuhan residents\u2019 depression and secondary trauma in the COVID-19 outbreak. Comput Human Behav 114:106524","journal-title":"Comput Human Behav"},{"issue":"5","key":"17395_CR16","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1016\/j.jadohealth.2020.07.042","volume":"68","author":"DT Beeres","year":"2020","unstructured":"Beeres DT, Andersson F, Vossen HGM, Galanti MR (2020) Social media and mental health among early adolescents in Sweden: a longitudinal study with 2-year follow-up (KUPOL Study). J Adolesc Health 68(5):953\u2013960","journal-title":"J Adolesc Health"},{"issue":"1","key":"17395_CR17","first-page":"37","volume":"2","author":"V Arul","year":"2019","unstructured":"Arul V, Sivakumar VG, Marimuthu R, Chakraborty B (2019) an approach for speech enhancement using deep convolutional neural network. Multimedia Res 2(1):37\u201344","journal-title":"Multimedia Res"},{"issue":"3","key":"17395_CR18","doi-asserted-by":"publisher","first-page":"39","DOI":"10.46253\/jcmps.v2i3.a5","volume":"2","author":"TC Srinivasa Rao","year":"2019","unstructured":"Srinivasa Rao TC, Tulasi Ram SS, Subrahmanyam JBV (2019) Enhanced deep convolutional neural network for fault signal recognition in the power distribution system. J Comput Mech, Power Syst Control 2(3):39\u201346","journal-title":"J Comput Mech, Power Syst Control"},{"issue":"3","key":"17395_CR19","first-page":"40","volume":"2","author":"SB Chandanapalli","year":"2019","unstructured":"Chandanapalli SB, Reddy ES, Lakshmi DR (2019) Convolutional neural network for water quality prediction in WSN. J Netw Commun Syst 2(3):40\u201347","journal-title":"J Netw Commun Syst"},{"key":"17395_CR20","doi-asserted-by":"publisher","first-page":"106645","DOI":"10.1016\/j.chb.2020.106645","volume":"116","author":"M Boer","year":"2021","unstructured":"Boer M, Stevens GW, Finkenauer C, de Looze ME, van den Eijnden RJ (2021) Social media use intensity, social media use problems, and mental health among adolescents: Investigating directionality and mediating processes. Comput Human Behav 116:106645","journal-title":"Comput Human Behav"},{"issue":"5","key":"17395_CR21","doi-asserted-by":"publisher","first-page":"7293","DOI":"10.1007\/s11042-022-13425-7","volume":"82","author":"DK Dewangan","year":"2023","unstructured":"Dewangan DK, Sahu SP (2023) Lane detection in intelligent vehicle system using optimal 2-tier deep convolutional neural network. Multimedia Tools Appl 82(5):7293\u20137317","journal-title":"Multimedia Tools Appl"},{"issue":"06","key":"17395_CR22","doi-asserted-by":"publisher","first-page":"2252002","DOI":"10.1142\/S0218001422520024","volume":"36","author":"DK Dewangan","year":"2022","unstructured":"Dewangan DK, Sahu SP (2022) Optimized convolutional neural network for road detection with structured contour and spatial information for intelligent vehicle system. Int J Pattern Recogn Artif Intell 36(06):2252002","journal-title":"Int J Pattern Recogn Artif Intell"},{"key":"17395_CR23","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1016\/j.future.2021.05.032","volume":"124","author":"A-S Uban","year":"2021","unstructured":"Uban A-S, Chulvi B, Rosso P (2021) An emotion and cognitive based analysis of mental health disorders from social media data. Futur Gener Comput Syst 124:480\u2013494","journal-title":"Futur Gener Comput Syst"},{"key":"17395_CR24","doi-asserted-by":"crossref","unstructured":"Tyagi T, Meena\u00a0S (2022) Online social networking and its relationship with mental health and emotional intelligence among female students. Clin Epidemiol Global Health 17:101131","DOI":"10.1016\/j.cegh.2022.101131"},{"key":"17395_CR25","doi-asserted-by":"crossref","unstructured":"Azhari A et al (2022) Social media use in female adolescents: Associations with anxiety, loneliness, and sleep disturbances. Acta Psychologica 229:103706","DOI":"10.1016\/j.actpsy.2022.103706"},{"key":"17395_CR26","doi-asserted-by":"crossref","unstructured":"Sharma A, Sanghvi K, Churi\u00a0P (2022) The impact of Instagram on young Adult's social comparison, colourism and mental health: Indian perspective. Int J Inform Manag Data Insights 2(1):100057","DOI":"10.1016\/j.jjimei.2022.100057"},{"key":"17395_CR27","doi-asserted-by":"crossref","unstructured":"Joshi D, Patwardhan M (2020) An analysis of mental health of social media users using unsupervised approach. Computers Human Behavior Reports 2:100036","DOI":"10.1016\/j.chbr.2020.100036"},{"key":"17395_CR28","doi-asserted-by":"crossref","unstructured":"Mann RB, Blumberg F (2022) Adolescents and social media: the effects of frequency of use, self-presentation, social comparison, and self esteem on possible self imagery. Acta Psychologica 228:103629","DOI":"10.1016\/j.actpsy.2022.103629"},{"key":"17395_CR29","doi-asserted-by":"crossref","unstructured":"Jia G et al (2022) Psychometric evaluation of the Chinese version of social anxiety scale for social media users and cross-sectional investigation into this disorder among college students. Compr Psychiatry 116:152328","DOI":"10.1016\/j.comppsych.2022.152328"},{"key":"17395_CR30","doi-asserted-by":"crossref","unstructured":"R\u00edssola EA, Aliannejadi M, Crestani F (2022) Mental disorders on online social media through the lens of language and behaviour: Analysis and visualisation. Inf Process Manag 59(3):102890","DOI":"10.1016\/j.ipm.2022.102890"},{"key":"17395_CR31","doi-asserted-by":"publisher","first-page":"6571","DOI":"10.3389\/fpsyg.2021.802821","volume":"12","author":"J Liu","year":"2022","unstructured":"Liu J, Shi M (2022) A hybrid feature selection and ensemble approach to identify depressed users in online social media. Front Psychol 12:6571","journal-title":"Front Psychol"},{"key":"17395_CR32","doi-asserted-by":"publisher","first-page":"9717","DOI":"10.1109\/ACCESS.2022.3144266","volume":"10","author":"E Lee","year":"2022","unstructured":"Lee E et al (2022) Racism detection by analyzing differential opinions through sentiment analysis of tweets using stacked ensemble gcr-nn model. IEEE Access 10:9717\u20139728","journal-title":"IEEE Access"},{"key":"17395_CR33","doi-asserted-by":"crossref","unstructured":"Hidayatullah AF, Muhammad Rifqi Ma\u2019Arif (2017) Pre-processing tasks in Indonesian Twitter messages. J Phys Conf Ser 801(1). IOP Publishing","DOI":"10.1088\/1742-6596\/801\/1\/012072"},{"key":"17395_CR34","doi-asserted-by":"publisher","first-page":"10329","DOI":"10.1016\/j.jbi.2019.103295","volume":"99","author":"D Zhao","year":"2019","unstructured":"Zhao D, Wang J, Lin H, Yang Z, Zhang Y (2019) Extracting drug\u2013drug interactions with hybrid bidirectional gated recurrent unit and graph convolutional network. J Biomed Inform 99:10329","journal-title":"J Biomed Inform"},{"key":"17395_CR35","unstructured":"Goodfellow IJ, Warde-Farley D, Mirza M, Courville A, Bengio Y (2013) Maxout networks. Proceedings of the 30th International Conference on Machine Learning, Atlanta, Georgia, USA"},{"key":"17395_CR36","first-page":"253","volume-title":"Convolutional networks and applications in vision","author":"Y LeCun","year":"2010","unstructured":"LeCun Y, Kavukvuoglu K, Farabet C (2010) Convolutional networks and applications in vision. In Circuits and Systems, International Symposium on, pp 253\u2013256"},{"issue":"Suppl 2","key":"17395_CR37","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.1007\/s00366-021-01292-z","volume":"38","author":"A Kaveh","year":"2022","unstructured":"Kaveh A, Zaerreza A, Hosseini SM (2022) An enhanced shuffled shepherd optimization algorithm for optimal design of large-scale space structures. Eng Comput 38(Suppl 2):1505\u20131526. https:\/\/doi.org\/10.1007\/s00366-021-01292-z","journal-title":"Eng Comput"},{"key":"17395_CR38","unstructured":"Furqan Mhd et al (2017) Performance of arithmetic crossover and heuristic crossover in genetic algorithm based on alpha parameter. IOSR J Comput Engineer (IOSR-JCE) 19(1):31\u201336"},{"key":"17395_CR39","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1155\/2022\/9404242","volume":"2022","author":"N Syed","year":"2022","unstructured":"Syed N, Jalali A (2022) Detection of types of mental illness through the social network using ensembled deep learning model. Comput Intell Neurosci 2022:6. https:\/\/doi.org\/10.1155\/2022\/9404242","journal-title":"Comput Intell Neurosci"},{"key":"17395_CR40","doi-asserted-by":"publisher","unstructured":"Kim J, Lee J, Park E, Han J (2020) A deep learning model for detecting mental illness from user content on social media. Sci Rep 10. https:\/\/doi.org\/10.1038\/s41598-020-68764-y","DOI":"10.1038\/s41598-020-68764-y"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17395-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17395-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17395-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T10:26:39Z","timestamp":1715768799000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17395-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,27]]},"references-count":40,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["17395"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17395-2","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,27]]},"assertion":[{"value":"18 March 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 October 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not Applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"The authors declare no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}