Detecting Reported Side Effects of COVID-19 Vaccines From Arabic Twitter (X) Data

被引:1
作者
Alhumayani, Maram K. [1 ]
Alhazmi, Huda N. [1 ]
机构
[1] Umm Al Qura Univ, Dept Comp Sci & Artificial Intelligence, Mecca 24382, Saudi Arabia
关键词
Arabic language; biterm topic modeling (BTM); COVID-19; vaccine; machine learning; NLP; side effects; support vector machine (SVM); Twitter (X);
D O I
10.1109/ACCESS.2024.3389655
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Vaccines might potentially cause side effects as any other drugs, which needs to be investigated and analyzed to identify the public safety concerns. The massive vaccination rollout against COVID-19 provoked discussion among people through social media platforms. Twitter (X), a popular social media platform, plays a significant role in disseminating information about COVID-19 vaccines and monitoring people's reports regarding vaccination side effects. The aim of this study is to mine Twitter (X) to identify self-reported side effects related to COVID-19 vaccines in Arabic language, compare their distribution among six vaccine types, and construct Arabic lexicon of symptoms. We collected the tweets posts in Arabic language after the distribution of COVID-19 vaccines, then we developed a workflow for identifying self-report symptoms using biterm topic modeling (BTM) and support vector machine (SVM) to extract the symptoms then cluster them in groups based on their co-occurrence. A total of 51 symptoms were extracted from 65,387 tweets that were reported 148,324 times. We performed a more in-depth analysis to investigate the symptoms that tend to occur simultaneously. The results show that the symptoms that more likely to occur together may indicate to a particular connection. The findings suggested that the social media conversation can provide a comprehensive depiction of symptoms that may complement what identified in clinical studies.
引用
收藏
页码:55367 / 55388
页数:22
相关论文
共 50 条
  • [21] Monitoring Mentions of COVID-19 Vaccine Side Effects on Japanese and Indonesian Twitter: Infodemiological Study
    Ferawati, Kiki
    Liew, Kongmeng
    Aramaki, Eiji
    Wakamiya, Shoko
    JMIR INFODEMIOLOGY, 2022, 2 (02):
  • [22] Arabic Twitter Conversation Dataset about the COVID-19 Vaccine
    Alhazmi, Huda
    DATA, 2022, 7 (11)
  • [23] Side Effects and Efficacy of COVID-19 Vaccines among the Egyptian Population
    Elgendy, Marwa O.
    El-Gendy, Ahmed O.
    Mahmoud, Sarah
    Mohammed, Tarek Yehia
    Abdelrahim, Mohamed E. A.
    Sayed, Ahmed M.
    VACCINES, 2022, 10 (01)
  • [24] Side effects of COVID-19 vaccines among Iranian healthcare workers: a retrospective cohort study
    Roudgari, Hassan
    Etemad, Koorosh
    Karami, Manoochehr
    Mostafavi, Farideh
    Ghorbani, Sahar Sotoodeh
    Babadi, Kosar Farhadi
    Rahimi, Elham
    Taherpour, Niloufar
    Masoom, Seyed Mahmood Fattahi
    Habibi, Masoud
    Kermanpour, Hossein
    Laripour, Reza
    Manoochehri, Omid
    Raeeszadeh, Mohammad
    Salimi, Alireza
    Shekarchi, Babak
    Tajernia, Ali
    Zafarghandi, Mohammad Reza
    Zali, Alireza
    Zarghi, Afshin
    Nazari, Seyed Saeed Hashemi
    JOURNAL OF INFECTION IN DEVELOPING COUNTRIES, 2024, 18 (04): : 532 - 541
  • [25] Personalized predictions of adverse side effects to the COVID-19 vaccines
    Jamshidi, E.
    Asgari, A.
    Mansouri, N.
    EUROPEAN RESPIRATORY JOURNAL, 2022, 60
  • [26] Side Effects of COVID-19 Vaccines Among Diabetic Subjects and Healthy Individuals
    Khan, Fareena
    Khan, Muhammad Taimur
    Zaman, Sana
    Mujtaba, Sadaf
    Batool, Aeliya
    Ghanghro, Zohra
    Anwar, Adnan
    Hashmi, Atif A.
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2023, 15 (03)
  • [27] COVID-19 Vaccine Sensing: Sentiment Analysis from Twitter Data
    Xu, Han
    Liu, Ruixin
    Luo, Ziling
    Xu, Minghua
    Wang, Bang
    2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2021, : 3200 - 3205
  • [28] Short-term side effects of COVID-19 vaccines: A cross-sectional study in Jordan
    Nassar, Razan, I
    Alnatour, Dalal
    Thiab, Samar
    Nassar, Ayman
    El-Hajji, Feras
    Basheti, Iman A.
    HUMAN VACCINES & IMMUNOTHERAPEUTICS, 2022, 18 (05)
  • [29] Worldwide COVID-19 Vaccines Sentiment Analysis Through Twitter Content
    Ansari, Md Tarique Jamal
    Khan, Naseem Ahmad
    ELECTRONIC JOURNAL OF GENERAL MEDICINE, 2021, 18 (06):
  • [30] The spectrum of side effects associated with COVID-19 vaccines in patients with inborn errors of immunity
    Ozdemiral, Cansu
    Cevik, Nadira Nabiyeva
    Yavuz, Gizem
    Gormez, Onuralp
    Zengin, Ayse Betul
    Esenboga, Saliha
    Karabulut, Erdem
    Cagdas, Deniz
    CLINICAL IMMUNOLOGY, 2024, 259