Monitoring global trends in Covid-19 vaccination intention and confidence: a social media-based deep learning study

Abstract

BackgroundThis study developed deep learning models to monitor global intention and confidence of Covid-19 vaccination in real time.MethodsWe collected 6.73 million English tweets regarding Covid-19 vaccination globally from January 2020 to February 2021. Fine-tuned Transformer-based deep learning models were used to classify tweets in real time as they relate to Covid-19 vaccination intention and confidence. Temporal and spatial trends were performed to map the global prevalence of Covid-19 vaccination intention and confidence, and public engagement on social media was analyzed.FindingsGlobally, the proportion of tweets indicating intent to accept Covid-19 vaccination declined from 64.49% on March to 39.54% on September 2020, and then began to recover, reaching 52.56% in early 2021. This recovery in vaccine acceptance was largely driven by the US and European region, whereas other regions experienced the declining trends in 2020. Intent to accept and confidence of Covid-19 vaccination were relatively high in South-East Asia, Eastern Mediterranean, and Western Pacific regions, but low in American, European, and African regions. 12.71% tweets expressed misinformation or rumors in South Korea, 14.04% expressed distrust in government in the US, and 16.16% expressed Covid-19 vaccine being unsafe in Greece, ranking first globally. Negative tweets, especially misinformation or rumors, were more engaged by twitters with fewer followers than positive tweets.InterpretationThis global real-time surveillance study highlights the importance of deep learning based social media monitoring to detect emerging trends of Covid-19 vaccination intention and confidence to inform timely interventions.FundingNational Natural Science Foundation of China.Research in contextEvidence before this studyWith COVID-19 vaccine rollout, each country should investigate its vaccination intention in local contexts to ensure massive vaccination. We searched PubMed for all articles/preprints until April 9, 2021 with the keywords “(“Covid-19 vaccines”[Mesh] OR Covid-19 vaccin*[TI]) AND (confidence[TI] OR hesitancy[TI] OR acceptance[TI] OR intention[TI])”. We identified more than 100 studies, most of which are country-level cross-sectional surveys, and the largest global survey of Covid-19 vaccine acceptance only covered 32 countries to date. However, how Covid-19 vaccination intention changes over time remain unknown, and many countries are not covered in previous surveys yet. A few studies assessed public sentiments towards Covid-19 vaccination using social media data, but only targeting limited geographical areas. There is a lack of real-time surveillance, and no study to date has globally monitored Covid-19 vaccination intention in real time.Added value of this studyTo our knowledge, this is the largest global monitoring study of Covid-19 vaccination intention and confidence with social media data in over 100 countries from the beginning of the pandemic to February 2021. This study developed deep learning models by fine-tuning a Bidirectional Encoder Representation from Transformer (BERT)-based model with 8000 manually-classified tweets, which can be used to monitor Covid-19 vaccination beliefs using social media data in real time. It achieves temporal and spatial analyses of the evolving beliefs to Covid-19 vaccines across the world, and also an insight for many countries not yet covered in previous surveys. This study highlights that the intention to accept Covid-19 vaccination have experienced a declining trend since the beginning of the pandemic in all world regions, with some regions recovering recently, though not to their original levels. This recovery was largely driven by the US and European region (EUR), whereas other regions experienced the declining trends in 2020. Intention to accept and confidence of Covid-19 vaccination were relatively high in South-East Asia region (SEAR), Eastern Mediterranean region (EMR), and Western Pacific region (WPR), but low in American region (AMR), EUR, and African region (AFR). Many AFR countries worried more about vaccine effectiveness, while EUR, AMR, and WPR concerned more about vaccine safety (the most concerns with 16.16% in Greece). Online misinformation or rumors were widespread in AMR, EUR, and South Korea (12.71%, ranks first globally), and distrust in government was more prevalent in AMR (14.04% in the US, ranks first globally). Our findings can be used as a reference point for survey data on a single country in the future, and inform timely and specific interventions for each country to address Covid-19 vaccine hesitancy.Implications of all the available evidenceThis global real-time surveillance study highlights the importance of deep learning based social media monitoring as a quick and effective method for detecting emerging trends of Covid-19 vaccination intention and confidence to inform timely interventions, especially in settings with limited sources and urgent timelines. Future research should build multilingual deep learning models and monitor Covid-19 vaccination intention and confidence in real time with data from multiple social media platforms.

Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination

“…A mostly similar approach was taken in the previous studies during the vaccination period to investigate the topics and themes discussed on social media. They have focused on vaccine hesitancy and antivaccine messages [ 46 ], vaccine efficacy and safety [ 23 ], and vaccination real-time surveillance [ 25 ]. This study provided a comparison of the public opinions and sentiments regarding the COVID-19 pandemic at the early stage of vaccination between two near states in the US, and it also showed how the local government responses reported on the news have shaped the social media discussion on different topics.…”

“…In addition, the common topics of the coronavirus-related Weibo texts were extracted and analyzed in terms of time and space [ 20 ]. Furthermore, in recent studies related to the COVID-19 and social media, the focus is on public opinion about the vaccination [ [21] , [22] , [23] ] and real-time surveillance based on social media monitoring to explore the trends of COVID-19 cases [ 24 ] and vaccinations [ 25 ] to support decision making and timely interventions. Villavicencio et al [ 26 ] studied the sentiments of people in Philippines on social media regarding the government efforts after delivering COVID-19 vaccines.…”

Uso de mídias sociais para monitorar o interesse em imunologia e chamar a atenção das pessoas para a saúde pública durante a pandemia de COVID-19 no Brasil

“…Apesar de ser uma ferramenta útil na educação e popularização da ciência, a internet é alvo de ataques de informações falsas e conteúdos duvidosos, como as Fake News. E, infelizmente, isso torna difícil a divulgação de material de qualidade [18][19][20][21][22][23]. Entretanto, atualmente a internet é a ferramenta mais viável para construir redes de comunicação com a capacidade de alcançar pessoas sem limitação de distância, e por este motivo, foi largamente utilizada no período mais crítico da pandemia da COVID-19 [24][25][26].…”

“…Entretanto, atualmente a internet é a ferramenta mais viável para construir redes de comunicação com a capacidade de alcançar pessoas sem limitação de distância, e por este motivo, foi largamente utilizada no período mais crítico da pandemia da COVID-19 [24][25][26]. A pandemia também contribuiu para a disponibilização de conteúdo científico para todos e, para controlar a boa informação se faz necessário que profissionais de saúde, profissionais médicos e professores trabalhem juntos para filtrar o conteúdo para a população (18,25,27). Considerando que a utilização de uma bibliografia confiável sobre imunologia era muito importante, este estudo criou uma conta nas redes sociais para atingir o maior número de pessoas possível.…”