The Longest Month: Analyzing COVID-19 Vaccination Opinions Dynamics From Tweets in the Month Following the First Vaccine Announcement

Cotfas, Liviu‐Adrian; Delcea, Camelia; Roxin, Ioan; Ioanăş, Corina; Gherai, Dana Simona; Tajariol, Federico

doi:10.1109/access.2021.3059821

Cited by 129 publications

(123 citation statements)

References 77 publications

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“…Sentiment results revealed that food supply and support from government was major problem face by the people and it concluded that most of the people showed negative sentiment while some users also posted positive opinions. The authors of another research paper [32] analyzed people's reactions regarding the coronavirus vaccine. The study collected 2,349,659 tweets for a month once the first dose vaccinated in the UK.…”

Section: Sentiment Polarity Assessment On Covid-19 Datamentioning

confidence: 99%

Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive

et al. 2021

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It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users’ tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.

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Section: Sentiment Polarity Assessment On Covid-19 Datamentioning

confidence: 99%

Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive

et al. 2021

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“…In general, existing studies have investigated people’s reactions towards COVID-19 vaccines, with a geographical emphasis on the United States [ 14 - 19 ]. Some papers have also studied other countries in the world, including China [ 20 ], South Africa [ 21 ], Australia [ 22 ], the United Kingdom [ 14 , 23 ], Canada [ 24 ], and Africa [ 25 ], and to a global scale [ 26 ]. However, the study period of these works is relatively limited to or predominantly focused on the early stage of the pandemic or up to the end of 2020.…”

Section: Introductionmentioning

confidence: 99%

Revealing Public Opinion Towards COVID-19 Vaccines With Twitter Data in the United States: Spatiotemporal Perspective

Hu¹,

Wang²,

Luo³

et al. 2021

J Med Internet Res

112

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Background The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance. Objective The aim of this study was to investigate public opinion and perception on COVID-19 vaccines in the United States. We investigated the spatiotemporal trends of public sentiment and emotion towards COVID-19 vaccines and analyzed how such trends relate to popular topics found on Twitter. Methods We collected over 300,000 geotagged tweets in the United States from March 1, 2020 to February 28, 2021. We examined the spatiotemporal patterns of public sentiment and emotion over time at both national and state scales and identified 3 phases along the pandemic timeline with sharp changes in public sentiment and emotion. Using sentiment analysis, emotion analysis (with cloud mapping of keywords), and topic modeling, we further identified 11 key events and major topics as the potential drivers to such changes. Results An increasing trend in positive sentiment in conjunction with a decrease in negative sentiment were generally observed in most states, reflecting the rising confidence and anticipation of the public towards vaccines. The overall tendency of the 8 types of emotion implies that the public trusts and anticipates the vaccine. This is accompanied by a mixture of fear, sadness, and anger. Critical social or international events or announcements by political leaders and authorities may have potential impacts on public opinion towards vaccines. These factors help identify underlying themes and validate insights from the analysis. Conclusions The analyses of near real-time social media big data benefit public health authorities by enabling them to monitor public attitudes and opinions towards vaccine-related information in a geo-aware manner, address the concerns of vaccine skeptics, and promote the confidence that individuals within a certain region or community have towards vaccines.

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“…In this context, analyzing public opinion related to the hesitancy towards COVID-19 vaccination can bring new insights on the evolution of this phenomenon, as it has been observed that negative attitudes were rising on Twitter in the month preceding the start of the vaccination process in UK [ 3 ]. The increase in the number of negative and hesitant tweets was 95.28% in the days following the UK authorization of the Pfizer BioNTech vaccine (2 December 2020–8 December 2020) compared to the period 9 November 2020–1 December 2020, in which the public was aware of the existence of a vaccine.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Vaccine Hesitancy in the Month Following the Start of the Vaccination Process

Cotfas

Delcea

Gherai

2021

IJERPH

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The occurrence of the novel coronavirus has changed a series of aspects related to people’s everyday life, the negative effects being felt all around the world. In this context, the production of a vaccine in a short period of time has been of great importance. On the other hand, obtaining a vaccine in such a short time has increased vaccine hesitancy and has activated anti-vaccination speeches. In this context, the aim of the paper is to analyze the dynamics of public opinion on Twitter in the first month after the start of the vaccination process in the UK, with a focus on COVID-19 vaccine hesitancy messages. For this purpose, a dataset containing 5,030,866 tweets in English was collected from Twitter between 8 December 2020–7 January 2021. A stance analysis was conducted after comparing several classical machine learning and deep learning algorithms. The tweets associated to COVID-19 vaccination hesitancy were examined in connection with the major events in the analyzed period, while the main discussion topics were determined using hashtags, n-grams and latent Dirichlet allocation. The results of the study can help the interested parties better address the COVID-19 vaccine hesitancy concerns.

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The Longest Month: Analyzing COVID-19 Vaccination Opinions Dynamics From Tweets in the Month Following the First Vaccine Announcement

Cited by 129 publications

References 77 publications

Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive

Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive

Revealing Public Opinion Towards COVID-19 Vaccines With Twitter Data in the United States: Spatiotemporal Perspective

COVID-19 Vaccine Hesitancy in the Month Following the Start of the Vaccination Process

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