ArticleIEEE access : practical innovations, open solutions2021
The Longest Month: Analyzing COVID-19 Vaccination Opinions Dynamics From Tweets in the Month Following the First Vaccine Announcement.
Article in IEEE access : practical innovations, open solutions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
26 citing papers in PubMed.
- Twitter communities are associated with changing user's opinion towards COVID-19 vaccine in Japan.Scientific reports · 2025Article
- Zero-shot cross-lingual stance detectionPeerJ. Computer science · 2025Article
- Article
- Analyzing information sharing behaviors during stance formation on COVID-19 vaccination among Japanese Twitter users.PloS one · 2024Article
- Unveiling Vaccine Hesitancy on Twitter: Analyzing Trends and Reasons during the Emergence of COVID-19 Delta and Omicron Variants.Vaccines · 2023Article
- Multivariate time series short term forecasting using cumulative data of coronavirus.Evolving systems · 2023Article
- A case study of using natural language processing to extract consumer insights from tweets in American cities for public health crises.BMC public health · 2023Article
- Examining Rural and Urban Sentiment Difference in COVID-19-Related Topics on Twitter: Word Embedding-Based Retrospective Study.Journal of medical Internet research · 2023Article
- A Comprehensive Analysis of COVID-19 Vaccine Discourse by Vaccine Brand on Twitter in Korea: Topic and Sentiment Analysis.Journal of medical Internet research · 2023Article
- Temporal analysis and opinion dynamics of COVID-19 vaccination tweets using diverse feature engineering techniques.PeerJ. Computer science · 2023Article
- ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning.PeerJ. Computer science · 2023Article
- A systematic review of machine learning techniques for stance detection and its applications.Neural computing & applications · 2023Review
- Uncovering the Reasons Behind COVID-19 Vaccine Hesitancy in Serbia: Sentiment-Based Topic Modeling.Journal of medical Internet research · 2022Article
- The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges.Healthcare (Basel, Switzerland) · 2022Review
- Dynamic Parameter Calibration Framework for Opinion Dynamics Models.Entropy (Basel, Switzerland) · 2022Article
- Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature.EClinicalMedicine · 2022Article
- Article
- Stance Analysis of Distance Education in the Kingdom of Saudi Arabia during the COVID-19 Pandemic Using Arabic Twitter Data.Sensors (Basel, Switzerland) · 2022Article
- Sentiment Analysis on COVID-19 Twitter Data Streams Using Deep Belief Neural Networks.Computational intelligence and neuroscience · 2022Article
- Automatically detecting and understanding the perception of COVID-19 vaccination: a middle east case study.Social network analysis and mining · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus outbreak has brought unprecedented measures, which forced the authorities to make decisions related to the instauration of lockdowns in the areas most hit by the pandemic. Social media has been an important support for people while passing through this difficult period. On November 9, 2020, when the first vaccine with more than 90% effective rate has been announced, the social media has reacted and people worldwide have started to express their feelings related to the vaccination, which was no longer a hypothesis but closer, each day, to become a reality. The present paper aims to analyze the dynamics of the opinions regarding COVID-19 vaccination by considering the one-month period following the first vaccine announcement, until the first vaccination took place in UK, in which the civil society has manifested a higher interest regarding the vaccination process. Classical machine learning and deep learning algorithms have been compared to select the best performing classifier. 2 349 659 tweets have been collected, analyzed, and put in connection with the events reported by the media. Based on the analysis, it can be observed that most of the tweets have a
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.