{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:52:45Z","timestamp":1743115965301,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030895075"},{"type":"electronic","value":"9783030895082"}],"license":[{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"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\/978-3-030-89508-2_76","type":"book-chapter","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T13:04:19Z","timestamp":1635339859000},"page":"590-597","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Application of Deep Learning Model Based on Big Data in Semantic Sentiment Analysis"],"prefix":"10.1007","author":[{"given":"Shiguang","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,28]]},"reference":[{"issue":"6","key":"76_CR1","doi-asserted-by":"publisher","first-page":"7819","DOI":"10.3934\/mbe.2020398","volume":"17","author":"Y Liu","year":"2020","unstructured":"Liu, Y., Lu, J., Yang, J., et al.: Sentiment analysis for e-commerce product reviews by deep learning model of Bert-BiGRU-Softmax. Math. Biosci. Eng. 17(6), 7819\u20137837 (2020)","journal-title":"Math. Biosci. Eng."},{"issue":"2","key":"76_CR2","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/s12652-018-1095-6","volume":"11","author":"B Liu","year":"2018","unstructured":"Liu, B.: Text sentiment analysis based on CBOW model and deep learning in big data environment. J. Ambient. Intell. Humaniz. Comput. 11(2), 451\u2013458 (2018). https:\/\/doi.org\/10.1007\/s12652-018-1095-6","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"76_CR3","doi-asserted-by":"crossref","unstructured":"Shrestha, N., Nasoz, F.: Deep learning sentiment analysis of Amazon.com reviews and ratings. Int. J. Soft Comput. Artif. Intell. Appl. 8(1), 01\u201315 (2019)","DOI":"10.5121\/ijscai.2019.8101"},{"issue":"12","key":"76_CR4","first-page":"205","volume":"10","author":"L Medrouk","year":"2017","unstructured":"Medrouk, L., Pappa, A.: Deep learning model for sentiment analysis in multi-lingual corpus. Lang. Linguist. Compass 10(12), 205\u2013212 (2017)","journal-title":"Lang. Linguist. Compass"},{"key":"76_CR5","doi-asserted-by":"crossref","unstructured":"Sui, L., Shang, L., Guo, X., et al.: Multifaceted sentiment analysis of public comments on the Dianping.com. In: Journal of Physics: Conference Series, vol. 1550, no. 3, p. 032052 (6pp) (2020)","DOI":"10.1088\/1742-6596\/1550\/3\/032052"},{"issue":"5","key":"76_CR6","doi-asserted-by":"publisher","first-page":"2050031","DOI":"10.1142\/S1469026820500315","volume":"19","author":"EH Mohamed","year":"2020","unstructured":"Mohamed, E.H., Moussa, E.S., Haggag, M.H.: An enhanced sentiment analysis framework based on pre-trained word embedding. Int. J. Comput. Intell. Appl. 19(5), 2050031 (2020)","journal-title":"Int. J. Comput. Intell. Appl."},{"issue":"6","key":"76_CR7","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.1049\/cje.2020.09.003","volume":"29","author":"G Cai","year":"2020","unstructured":"Cai, G., Lyu, G., Lin, Y., et al.: Multi-level deep correlative networks for multi-modal sentiment analysis. Chin. J. Electron. 29(6), 1025\u20131038 (2020)","journal-title":"Chin. J. Electron."},{"key":"76_CR8","doi-asserted-by":"crossref","unstructured":"Kumar, A., Srinivasan, K., Cheng, W.H., et al.: Hybrid context enriched deep learning model for fine-grained sentiment analysis in textual and visual semiotic modality social data. Inf. Process. Manag. 57(1), 102141.1\u2013102141.25 (2020)","DOI":"10.1016\/j.ipm.2019.102141"},{"key":"76_CR9","doi-asserted-by":"crossref","unstructured":"Ying, O.J., Zabidi, M., Ramli, N., et al.: Sentiment analysis of informal Malay tweets with deep learning. IAES Int. J. Artif. Intell. (IJ-AI) 9(2), 212 (2020)","DOI":"10.11591\/ijai.v9.i2.pp212-220"},{"issue":"8","key":"76_CR10","doi-asserted-by":"publisher","first-page":"43","DOI":"10.21833\/ijaas.2017.08.007","volume":"4","author":"A Altaher","year":"2017","unstructured":"Altaher, A.: Hybrid approach for sentiment analysis of Arabic tweets based on deep learning model and features weighting. Int. J. Adv. Appl. Sci. 4(8), 43\u201349 (2017)","journal-title":"Int. J. Adv. Appl. Sci."},{"issue":"11","key":"76_CR11","first-page":"32","volume":"50","author":"Z Jin","year":"2018","unstructured":"Jin, Z., Han, Y., Zhu, Q.: A sentiment analysis model with the combination of deep learning and ensemble learning. Harbin Gongye Daxue Xuebao\/J. Harbin Inst. Technol. 50(11), 32\u201339 (2018)","journal-title":"Harbin Gongye Daxue Xuebao\/J. Harbin Inst. Technol."},{"key":"76_CR12","first-page":"1","volume":"4","author":"ES Alamoudi","year":"2021","unstructured":"Alamoudi, E.S., Alghamdi, N.S.: Sentiment classification and aspect-based sentiment analysis on yelp reviews using deep learning and word embeddings. J. Decis. Syst. 4, 1\u201323 (2021)","journal-title":"J. Decis. Syst."}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-89508-2_76","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T13:11:02Z","timestamp":1635340262000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-89508-2_76"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,28]]},"ISBN":["9783030895075","9783030895082"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-89508-2_76","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2021,10,28]]},"assertion":[{"value":"28 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SPIoT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"spiot2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.spiot.net.cn\/SPIOT2021","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}