{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:52:30Z","timestamp":1742914350345,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":10,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811929472"},{"type":"electronic","value":"9789811929489"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-19-2948-9_31","type":"book-chapter","created":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T06:03:51Z","timestamp":1662012231000},"page":"323-334","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Analysis of COVID-19 Epidemic Disease Dynamics Using Deep Learning"],"prefix":"10.1007","author":[{"given":"K.","family":"Nirmala Devi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Shanthi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K.","family":"Hemanandhini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Haritha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Aarthy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,2]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Alhuri LA, Aljohani HR, Almutairi RM, Haron F (2020) Sentiment analysis of COVID-19 on Saudi trending hashtags using recurrent neural network. In: 2020 13th International conference on developments in eSystems engineering (DeSE). IEEE, pp 299\u2013304","key":"31_CR1","DOI":"10.1109\/DeSE51703.2020.9450746"},{"key":"31_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106754","volume":"97","author":"K Chakraborty","year":"2020","unstructured":"Chakraborty K, Bhatia S (2020) Sentiment analysis of COVID-19 tweets by deep learning classifiers\u2014a study to show how popularity is affecting accuracy in social media. Appl Soft Comput 97:106754","journal-title":"Appl Soft Comput"},{"doi-asserted-by":"crossref","unstructured":"Basiri ME, Nemati S, Abdar M, Asadi S, Acharrya UR (2021) A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets","key":"31_CR3","DOI":"10.1016\/j.knosys.2021.107242"},{"key":"31_CR4","doi-asserted-by":"publisher","first-page":"181074","DOI":"10.1109\/ACCESS.2020.3027350","volume":"8","author":"AS Imran","year":"2020","unstructured":"Imran AS, Daudpota SM, Kastrati Z, Batra R (2020) Cross-cultural polarity and emotion detection using sentiment analysis and deep learning on COVID-19 related tweets. IEEE Access 8:181074\u2013181090","journal-title":"IEEE Access"},{"doi-asserted-by":"crossref","unstructured":"Kaur H, Ahsaan SU, Alankar B, Chang V (2021) A proposed sentiment analysis deep learning algorithm for analyzing COVID-19 Tweets. Inf Syst Front, 1\u201313","key":"31_CR5","DOI":"10.1007\/s10796-021-10135-7"},{"issue":"9","key":"31_CR6","first-page":"14533","volume":"83","author":"K Nirmaladevi","year":"2020","unstructured":"Nirmaladevi K, Shanthi S, Agila T, Dharani RT, Dhivyapriya P (2020) Analysis and prediction of diabetes using machine learning. Test Eng Manage 83(9):14533\u201314538","journal-title":"Test Eng Manage"},{"doi-asserted-by":"crossref","unstructured":"Shanthi S, Nirmaladevi K, Pyingkodi M, Dharanesh K, Gowthaman T, Harsavardan B (2021) Machine learning approach for detection of keratoconus. IOP Conf Ser Mater Sci Eng 1055(1):012112. IOP Publishing","key":"31_CR7","DOI":"10.1088\/1757-899X\/1055\/1\/012112"},{"doi-asserted-by":"crossref","unstructured":"Mengistie TT, Kumar D (2021) Deep learning based sentiment analysis on COVID-19 public reviews. In: 2021 International conference on artificial intelligence in information and communication (ICAIIC). IEEE, pp 444\u2013449","key":"31_CR8","DOI":"10.1109\/ICAIIC51459.2021.9415191"},{"key":"31_CR9","doi-asserted-by":"publisher","first-page":"97079","DOI":"10.1109\/ACCESS.2021.3094173","volume":"9","author":"DS Abdelminaam","year":"2021","unstructured":"Abdelminaam DS, Neggaz N, Gomaa IAE, Ismail FH, Elsawy AA (2021) ArabicDialects: an efficient framework for Arabic dialects opinion mining on Twitter using optimized deep neural networks. IEEE Access 9:97079\u201397099","journal-title":"IEEE Access"},{"doi-asserted-by":"crossref","unstructured":"Roy A, Ojha M (2020) Twitter sentiment analysis using deep learning models. In: 2020 IEEE 17th India Council international conference (INDICON). IEEE, pp 1\u20136","key":"31_CR10","DOI":"10.1109\/INDICON49873.2020.9342279"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Proceedings of 7th International Conference on Harmony Search, Soft Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-2948-9_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T06:21:07Z","timestamp":1662013267000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-2948-9_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811929472","9789811929489"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-2948-9_31","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"2 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}