Anti-intellectualism (resentment, hostility, and mistrust of experts) has become a growing concern during the pandemic. Using topic modeling and supervised machine learning, this study examines the elements and sources of anti-Fauci tweets as a case of anti-intellectual discourse on social media. Based on the theoretical framework of science-related populism, we identified three anti-intellectual discursive elements in anti-Fauci tweets: people-scientist antagonism, delegitimizing the motivation of scientists, and delegitimizing the knowledge of scientists. Delegitimizing the motivation of scientists appeared the most in anti-Fauci tweets. Politicians, conservative news media, and non-institutional actors (e.g. individuals and grassroots advocacy organizations) co-constructed the production and circulation of anti-intellectual discourses on Twitter. Anti-intellectual discourses resurged even under Twitter’s content moderation mechanism. We discuss theoretical and practical implications for building public trust in scientists, effective science communication, and content moderation policies on social media.

Background: Many countries show low COVID-19 vaccination rates despite high levels of readiness and delivery of vaccines. The public’s misperceptions, hesitancy, and negative emotions toward vaccines are psychological factors discouraging vaccination. At the individual level, studies have revealed negative perceptual/behavioral outcomes of COVID-19 information exposure via social media where misinformation and vaccine fear flood. Objective: This study extends research context to the global level and investigates social media discourse on the COVID-19 vaccine and its association with vaccination rates of 192 countries in the world. Methods: COVID-19 vaccine tweets were compared by country in terms of (1) the number per million Twitter users, (2) mentions of adverse events—death, side-effects, blood clots, (3) negative sentiment (vs. positive), and (4) fear, sadness, or anger emotions (vs. joy). Artificial intelligence (AI) was adopted to classify sentiment and emotions. Such tweets and covariates (COVID-19 morbidity and mortality rates, GDP, population size and density, literacy rate, democracy index, institutional quality, human development index) were tested as predictors of vaccination rates in countries. Results: Over 21.3 million COVID-19 vaccine tweets posted between November 2020 and August 2021 worldwide were included in our analysis. The global average of COVID-19 vaccine tweets mentioning adverse events was 2% for ‘death’, 1.15% for ‘side-effects’, and 0.80% for ‘blood clots’. Negative sentiment appeared 1.90 times more frequently than positive sentiment. Fear, anger, or sadness appeared 0.70 times less frequently than joy. The mention of ‘side-effects’ and fear/sadness/anger emotions appeared as significant predictors of vaccination rates, along with the human development index. Conclusions: Our findings indicate that global efforts to combat misinformation, address negative emotions, and promote positive languages surrounding COVID-19 vaccination on social media may help increase global vaccination uptakes.

Building on the global trend of celebrity activism and concept of celebrity capital, this study qualitatively examines Twitter posts of the Bollywood celebrities. The aim of this analysis was to identify varying discourses about the 2020–21 Indian farmers’ protest as celebrities are considered significant players of discourse building and social movements. The thematic analysis showed that pro- and anti-farmers’ protest celebrities used rhetorical and explanatory support to build their discourses. Some celebrities even engaged in celebrity-shaming and name-calling to urge fellow Bollywood celebrities to support or stop supporting the protesters. Findings suggest that global trend of celebrity activism is becoming more visible in Bollywood and celebrities are using their influence to support or oppose social movements like the farmers’ protest.

BACKGROUND Many countries show low COVID-19 vaccination rates despite high levels of readiness and delivery of vaccines. The public’s misperceptions, hesitancy, and negative emotions towards vaccines are psychological factors discouraging vaccination. At the individual level, studies have revealed negative perceptual/behavioral outcomes of COVID-19 information exposure via social media where misinformation and vaccine fear flood. OBJECTIVE This study extends research context to the global level and investigates social media discourse on COVID-19 vaccine and its association with vaccination rates of 192 countries in the world. METHODS COVID-19 vaccine tweets were compared by country in terms of (1) the number per million Twitter users, (2) mentions of adverse events - death, side effect, blood clots, (3) negative sentiment (vs. positive), and (4) fear, sadness, or anger emotions (vs. joy). Artificial intelligence (AI) was adopted to classify sentiment and emotions. Such tweets and covariates (COVID-19 morbidity and mortality rates, GDP, population size and density, literacy rate, democracy index, institutional quality, human development index) were tested as predictors of vaccination rates in countries. RESULTS Over 21.3 million COVID-19 vaccine tweets posted between November 2020 and August 2021 worldwide were included in our analysis. The global average of tweets mentioning adverse events was 2% for ‘death’, 1.15% for ‘side effects’, and 0.80% for ‘blood clots.’ Negative sentiment appeared 1.90 times more frequently than positive ones. Fear, anger, or sadness appeared 0.70 times less frequently than joy. The ‘side effect’ mention and fear/sadness/anger emotions appeared as significant predictors of vaccination rates with human development index. CONCLUSIONS Our findings indicate global efforts to combat misinformation, decrease negative emotions, and promote positive languages surrounding COVID-19 vaccination on social media may help increase global vaccination uptakes.

We investigate social media discourses on the relationship between cancer and COVID-19 vaccines focusing on the key textual topics, themes reflecting the voice of cancer community, authors who contribute to the discourse, and valence toward vaccines. We analyzed 6,427 tweets about cancer and COVID-19 vaccines, posted from when vaccines were approved in the U.S. (December 2020) to the February 2022. We mixed quantitative text mining, manual coding and statistical analysis, and inductive qualitative thematic analysis. Nearly 16% of the tweets posted by a cancer community member mentioned about refusal or delay of their vaccination at the state/local level during the initial rollout despite the CDC’s recommendation to prioritize adults with high-risk medical conditions. Most tweets posted by cancer patients (pro = 82.4% vs. anti = 5.1%) and caregivers (pro = 89.2% vs. anti = 4.2%) showed positive valence toward vaccines and advocated for vaccine uptake increase among cancer patients and the general population. Vaccine hesitancy, self-reported adverse events, and COVID-19 disruption of cancer treatment also appeared as key themes. The cancer community called for actions to improve vaccination procedures to become safe and accessible especially for elderly cancer patients, develop COVID-19 vaccines suitable for varying type, stage, and treatment of cancer, and advance cancer vaccines. Future research should continue surveilling conversations around continuous impacts of COVID-19 interference with the cancer control continuum, beyond vaccination, focusing on the voice and concern of cancer community.

Prescription drug misuse and opioid overdose have become one of the most serious health crises in the US health system. In this study, we examined Last Week Tonight as hosted by John Oliver in order to explore topics, sentiments, and reactions by referring to online comments on YouTube. Using an unsupervised machine learning approach, we analyzed 33,741 user generated comments taken from three selected episodes published between 2016 and 2021. Our results revealed 13 topics: the politicization of the opioid crisis, side effects of opioid use, seeking help, legal issues, reactions to the John Oliver show, drug addiction, the US in comparison with other countries, case settlements, the drug business, addiction and pharmaceutical companies, profitability of companies from deaths, drugs and elections, as well as general awareness and education. In addition, we found that opioid side effects, seeking help, and the drug business had received the highest user engagements in terms of likes and replies. Our study suggests that comments with positive sentiments were more likely to cause a more widespread engagement from YouTube users than negative comments.