{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,7]],"date-time":"2025-04-07T03:10:06Z","timestamp":1743995406202,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031877681","type":"print"},{"value":"9783031877698","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-87769-8_12","type":"book-chapter","created":{"date-parts":[[2025,4,7]],"date-time":"2025-04-07T02:36:40Z","timestamp":1743993400000},"page":"129-140","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Arabic Sentiment Analysis Leveraging Hybrid Word Embeddings with\u00a0Deep Learning Techniques"],"prefix":"10.1007","author":[{"given":"Abdulrahman","family":"Alharbi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nabin","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farookh","family":"Hussain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,8]]},"reference":[{"issue":"1","key":"12_CR1","doi-asserted-by":"publisher","first-page":"119","DOI":"10.26555\/jiteki.v9i1.25813","volume":"9","author":"A Adam","year":"2023","unstructured":"Adam, A., Setiawan, E.B.: Social media sentiment analysis using convolutional neural network (CNN) DAN gated recurrent unit (GRU). Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) 9(1), 119\u2013131 (2023)","journal-title":"Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)"},{"key":"12_CR2","doi-asserted-by":"crossref","unstructured":"Alahmary, R.M., Al-Dossari, H.Z., Emam, A.Z.: Sentiment analysis of Saudi dialect using deep learning techniques. In: 2019 International Conference on Electronics, Information, and Communication (ICEIC), pp. 1\u20136 (2019)","DOI":"10.23919\/ELINFOCOM.2019.8706408"},{"issue":"10","key":"12_CR3","doi-asserted-by":"publisher","first-page":"9710","DOI":"10.1016\/j.jksuci.2021.12.004","volume":"34","author":"AM Alayba","year":"2022","unstructured":"Alayba, A.M., Palade, V.: Leveraging Arabic sentiment classification using an enhanced CNN-LSTM approach and effective Arabic text preparation. J. King Saud Univ.-Comput. Inf. Sci. 34(10), 9710\u20139722 (2022)","journal-title":"J. King Saud Univ.-Comput. Inf. Sci."},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"Alharbi, A., Sharma, N.: Challenges and approaches in Arabic sentiment analysis: a review. In: International Conference on Data Science and Communication, pp. 499\u2013519. Springer, Cham (2023)","DOI":"10.1007\/978-981-99-5435-3_36"},{"key":"12_CR5","doi-asserted-by":"crossref","unstructured":"Alharbi, A., Sharma, N., Hussain, F.: Arabic sentiment analysis with social network data: a comparative study. In: 2024 IEEE International Conference on e-Business Engineering (ICEBE), pp. 87\u201394. IEEE (2024)","DOI":"10.1109\/ICEBE62490.2024.00022"},{"key":"12_CR6","unstructured":"Alqurashi, S., Hamoui, B., Alashaikh, A., Alhindi, A., Alanazi, E.: Eating garlic prevents Covid-19 infection: detecting misinformation on the Arabic content of twitter. arXiv preprint arXiv:2101.05626 (2021)"},{"key":"12_CR7","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1162\/tacl_a_00051","volume":"5","author":"P Bojanowski","year":"2017","unstructured":"Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. Assoc. Comput. Linguist. 5, 135\u2013146 (2017)","journal-title":"Trans. Assoc. Comput. Linguist."},{"issue":"6","key":"12_CR8","doi-asserted-by":"publisher","first-page":"126","DOI":"10.3390\/computers12060126","volume":"12","author":"N Elhassan","year":"2023","unstructured":"Elhassan, N., et al.: Arabic sentiment analysis based on word embeddings and deep learning. Computers 12(6), 126 (2023)","journal-title":"Computers"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Elsamadony, O., Keshk, A., Abdelatey, A.: Sentiment analysis for Arabic language using word embedding. In: 2021 17th International Computer Engineering Conference (ICENCO), pp. 51\u201356. IEEE (2021)","DOI":"10.1109\/ICENCO49852.2021.9698960"},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Gayed, S., Mallat, S., Zrigui, M.: Exploring word embedding for Arabic sentiment analysis. In: Asian Conference on Intelligent Information and Database Systems, pp. 92\u2013101. Springer, Cham (2022)","DOI":"10.1007\/978-981-19-8234-7_8"},{"key":"12_CR11","unstructured":"Grave, E., Bojanowski, P., Gupta, P., Joulin, A., Mikolov, T.: Learning word vectors for 157 languages. arXiv preprint arXiv:1802.06893 (2018)"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Kancharapu, R., A\u00a0Ayyagari, S.N.: A comparative study on word embedding techniques for suicide prediction on Covid-19 tweets using deep learning models. Int. J. Inf. Technol. 15(6), 3293\u20133306 (2023)","DOI":"10.1007\/s41870-023-01338-z"},{"key":"12_CR13","doi-asserted-by":"publisher","first-page":"28162","DOI":"10.1109\/ACCESS.2023.3259107","volume":"11","author":"J Khan","year":"2023","unstructured":"Khan, J., Ahmad, N., Khalid, S., Ali, F., Lee, Y.: Sentiment and context-aware hybrid DNN with attention for text sentiment classification. IEEE Access 11, 28162\u201328179 (2023)","journal-title":"IEEE Access"},{"key":"12_CR14","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.procs.2022.12.400","volume":"218","author":"U Mahadevaswamy","year":"2023","unstructured":"Mahadevaswamy, U., Swathi, P.: Sentiment analysis using bidirectional LSTM network. Procedia Comput. Sci. 218, 45\u201356 (2023)","journal-title":"Procedia Comput. Sci."},{"issue":"2","key":"12_CR15","doi-asserted-by":"publisher","first-page":"588","DOI":"10.3390\/app14020588","volume":"14","author":"E Memi\u015f","year":"2024","unstructured":"Memi\u015f, E., Akarkam\u00e7\u0131, H., Yeniad, M., Rahebi, J., Lopez-Guede, J.M.: Comparative study for sentiment analysis of financial tweets with deep learning methods. Appl. Sci. 14(2), 588 (2024)","journal-title":"Appl. Sci."},{"key":"12_CR16","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)"},{"key":"12_CR17","doi-asserted-by":"crossref","unstructured":"Ouchene, L., Bessou, S.: Fasttext embedding and LSTM for sentiment analysis: an empirical study on Algerian tweets. In: 2023 International Conference on Information Technology (ICIT), pp. 51\u201355. IEEE (2023)","DOI":"10.1109\/ICIT58056.2023.10226060"},{"key":"12_CR18","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1016\/j.procs.2017.10.117","volume":"117","author":"AB Soliman","year":"2017","unstructured":"Soliman, A.B., Eissa, K., El-Beltagy, S.R.: Aravec: a set of Arabic word embedding models for use in Arabic NLP. Procedia Comput. Sci. 117, 256\u2013265 (2017)","journal-title":"Procedia Comput. Sci."},{"issue":"2","key":"12_CR19","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s41060-021-00242-8","volume":"11","author":"F Torregrossa","year":"2021","unstructured":"Torregrossa, F., Allesiardo, R., Claveau, V., Kooli, N., Gravier, G.: A survey on training and evaluation of word embeddings. Int. J. Data Sci. Anal. 11(2), 85\u2013103 (2021). https:\/\/doi.org\/10.1007\/s41060-021-00242-8","journal-title":"Int. J. Data Sci. Anal."},{"key":"12_CR20","doi-asserted-by":"crossref","unstructured":"Wu, Y., Jin, Z., Shi, C., Liang, P., Zhan, T.: Research on the application of deep learning-based BERT model in sentiment analysis. arXiv preprint arXiv:2403.08217 (2024)","DOI":"10.54254\/2755-2721\/67\/2024MA"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-87769-8_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,7]],"date-time":"2025-04-07T02:36:53Z","timestamp":1743993413000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-87769-8_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031877681","9783031877698"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-87769-8_12","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"value":"2367-4512","type":"print"},{"value":"2367-4520","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"8 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Barcelona","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"39","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina0","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}