Worldwide COVID-19 Vaccines Sentiment Analysis Through Twitter Content

Ansari, Tarique Mahmood; Khan, Naseem

doi:10.29333/ejgm/11316

Cited by 46 publications

(26 citation statements)

References 31 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Feature selection is a standard procedure to filter or select the important attributes that determine the sentiments of the public [ 25 ], and we further pinpointed the sentiment determinants related to the vaccine booster by using multivariance logistics regression. This study’s procedures are standard across other infectious diseases [ 15 , 16 , 25 ], and the results of our model showing two representative attributes—“pfizer” and “mix”—were supported by Ahmed et al [ 13 ], Aygun et al [ 16 ], Marcec et al [ 17 ], etc., in that the brand of vaccine played a crucial role when the public plan was to administer an additional vaccine booster.…”

Section: Discussionsupporting

confidence: 78%

“…Nonetheless, topic modeling, extraction, or sentiments analysis on vaccine boosters have yet to be studied. Ansari et al [ 15 ] used COVID-19 vaccine related tweets and conducted sentiment analysis to uncover the latest information on the effect of location and gender on the current vaccination. Aygun et al [ 16 ] used aspect-based sentiment analysis for Twitter users from the USA, UK, Canada, Turkey, France, Germany, Spain, and Italy and used four different aspects (policy, health, media, and other) and four different BERT models (mBERT-base, BioBERT, ClinicalBERT, and BERTurk) to understand peoples’ views about vaccination and types of vaccines.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Text Mining and Determinants of Sentiments towards the COVID-19 Vaccine Booster of Twitter Users in Malaysia

2022

View full text Add to dashboard Cite

Vaccination is the primary preventive measure against the COVID-19 infection, and an additional vaccine dosage is crucial to increase the immunity level of the community. However, public bias, as reflected on social media, may have a significant impact on the vaccination program. We aim to investigate the attitudes to the COVID-19 vaccination booster in Malaysia by using sentiment analysis. We retrieved 788 tweets containing COVID-19 vaccine booster keywords and identified the common topics discussed in tweets that related to the booster by using latent Dirichlet allocation (LDA) and performed sentiment analysis to understand the determinants for the sentiments to receiving the vaccination booster in Malaysia. We identified three important LDA topics: (1) type of vaccination booster; (2) effects of vaccination booster; (3) vaccination program operation. The type of vaccination further transformed into attributes of “az”, “pfizer”, “sinovac”, and “mix” for determinants’ assessments. Effect and type of vaccine booster associated stronger than program operation topic for the sentiments, and “pfizer” and “mix” were the strongest determinants of the tweet’s sentiments after the Boruta feature selection and validated from the performance of regression analysis. This study provided a comprehensive workflow to retrieve and identify important healthcare topic from social media.

show abstract

Section: Discussionsupporting

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Text Mining and Determinants of Sentiments towards the COVID-19 Vaccine Booster of Twitter Users in Malaysia

2022

View full text Add to dashboard Cite

show abstract

“…These categories pertain to the prevailing attitude of the persons whom Retweets are being analysed by Javed et al [12] . Ansari et al [13] , they have analysed COVID-19 immunization retweets to offer an assessment of the government's sentiments to ongoing immunization drives. Investigations on sentiment classification were also conducted in order to reveal new knowledge regarding the effects of location and gender including [3] , [14] , [15] .…”

Section: Related Workmentioning

confidence: 99%

COVID-19 vaccine sentiment analysis using public opinions on Twitter

Chinnasamy¹,

Suresh²,

Ramprathap³

et al. 2022

Materials Today: Proceedings

View full text Add to dashboard Cite

“…IDSs should change and continually adjust to all of these new threats and assault techniques. The challenge on which scholars have been researching for decades is how to construct effective, efficient, and responsive IDSs [11][12][13][14][15].…”

Section: Figure 1 General Architecture Of Intrusion-detection System ...mentioning

confidence: 99%

Effectiveness Evaluation of Different IDSs Using Integrated Fuzzy MCDM Model

et al. 2022

Self Cite

View full text Add to dashboard Cite

Cyber-attacks are becoming progressively complicated; hence, the functional issues of intrusion-detection systems (IDSs) present ever-growing challenges. Failing to detect intrusions may jeopardize the trustworthiness of security services, such as privacy preservation, authenticity, and accessibility. To fight these risks, different organizations nowadays use a variety of approaches, techniques, and technologies to safeguard the systems’ credibility. Establishing policies and procedures, raising user awareness, implementing firewall and verification systems, controlling system access, and building computer-issue management groups are all examples of safeguarding methods. There is a lack of sufficient emphasis on the effectiveness of intrusion-detection systems. In enterprises, IDS is used to analyze the potentially dangerous activities taking place within the technological settings. The selection of efficient IDS is a challenging task for organizations. This research evaluates the impact of five popular IDSs for their efficiency and effectiveness in information security. The authors used the fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS)-based integrated multi-criteria decision-making (MCDM) methodology to evaluate the efficacy of the popular IDSs. The findings of this research suggest that most of the IDSs appear to be highly potential tools. Even though Snort is extensively deployed, Suricata has a substantial advantage over Snort. Suricata uses multi-threading functionality in comparison to Snort to boost the processing performance.

show abstract

Worldwide COVID-19 Vaccines Sentiment Analysis Through Twitter Content

Cited by 46 publications

References 31 publications

Text Mining and Determinants of Sentiments towards the COVID-19 Vaccine Booster of Twitter Users in Malaysia

Text Mining and Determinants of Sentiments towards the COVID-19 Vaccine Booster of Twitter Users in Malaysia

COVID-19 vaccine sentiment analysis using public opinions on Twitter

Effectiveness Evaluation of Different IDSs Using Integrated Fuzzy MCDM Model

Contact Info

Product

Resources

About