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Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy.
Alamoodi, A H; Zaidan, B B; Al-Masawa, Maimonah; Taresh, Sahar M; Noman, Sarah; Ahmaro, Ibraheem Y Y; Garfan, Salem; Chen, Juliana; Ahmed, M A; Zaidan, A A; Albahri, O S; Aickelin, Uwe; Thamir, Noor N; Fadhil, Julanar Ahmed; Salahaldin, Asmaa.
  • Alamoodi AH; Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia. Electronic address: Alamoodi@fskik.upsi.edu.my.
  • Zaidan BB; Future Technology Research Center, College of Future, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, ROC.
  • Al-Masawa M; Centre for Tissue Engineering and Regenerative Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latif, 56000, Kuala Lumpur, Malaysia.
  • Taresh SM; Department of Kindergarten Educational Psychology, Taiz University, Yemen.
  • Noman S; Department of Community Health, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Malaysia.
  • Ahmaro IYY; Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine.
  • Garfan S; Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia.
  • Chen J; The University of Sydney, Charles Perkins Centre, Discipline of Nutrition and Dietetics, School of Life and Environmental Sciences, Camperdown, New South Wales, Australia; Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Australia; Healthy Weight Clinic
  • Ahmed MA; Computer Science and Mathematics College, Tikrit University, Iraq.
  • Zaidan AA; Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia.
  • Albahri OS; Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia.
  • Aickelin U; School of Computing and Information Systems, University of Melbourne, 700 Swanston Street, Victoria, 3010, Australia.
  • Thamir NN; Department of Computer Science, University of Baghdad, Iraq.
  • Fadhil JA; Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), 43400 Serdang, Malaysia.
  • Salahaldin A; College of Graduate Studies, Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia.
Comput Biol Med ; 139: 104957, 2021 12.
مقالة ي الانجليزية | MEDLINE | ID: covidwho-1525748
ABSTRACT
A substantial impediment to widespread Coronavirus disease (COVID-19) vaccination is vaccine hesitancy. Many researchers across scientific disciplines have presented countless studies in favor of COVID-19 vaccination, but misinformation on social media could hinder vaccination efforts and increase vaccine hesitancy. Nevertheless, studying people's perceptions on social media to understand their sentiment presents a powerful medium for researchers to identify the causes of vaccine hesitancy and therefore develop appropriate public health messages and interventions. To the best of the authors' knowledge, previous studies have presented vaccine hesitancy in specific cases or within one scientific discipline (i.e., social, medical, and technological). No previous study has presented findings via sentiment analysis for multiple scientific disciplines as follows (1) social, (2) medical, public health, and (3) technology sciences. Therefore, this research aimed to review and analyze articles related to different vaccine hesitancy cases in the last 11 years and understand the application of sentiment analysis on the most important literature findings. Articles were systematically searched in Web of Science, Scopus, PubMed, IEEEXplore, ScienceDirect, and Ovid from January 1, 2010, to July 2021. A total of 30 articles were selected on the basis of inclusion and exclusion criteria. These articles were formed into a taxonomy of literature, along with challenges, motivations, and recommendations for social, medical, and public health and technology sciences. Significant patterns were identified, and opportunities were promoted towards the understanding of this phenomenon.
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النص الكامل: متاح مجموعة: قواعد البيانات الدولية قاعدة البيانات: MEDLINE الموضوع الرئيسي: COVID-19 Vaccines / COVID-19 نوع الدراسة: المراجعات / مراجعة منهجية / تحليل ميتا المواضيع: اللقاحات المحددات: البشر اللغة: الانجليزية مجلة: Comput Biol Med السنة: 2021 نوع: مقالة

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النص الكامل: متاح مجموعة: قواعد البيانات الدولية قاعدة البيانات: MEDLINE الموضوع الرئيسي: COVID-19 Vaccines / COVID-19 نوع الدراسة: المراجعات / مراجعة منهجية / تحليل ميتا المواضيع: اللقاحات المحددات: البشر اللغة: الانجليزية مجلة: Comput Biol Med السنة: 2021 نوع: مقالة