Measuring COVID-19 Related Media Consumption on Twitter (preprint)

The COVID-19 pandemic has been affecting the world dramatically ever since 2020. The minimum availability of physical interactions during the lockdown has caused more and more people to turn to online activities on social media platforms. These platforms have provided essential updates regarding the pandemic, serving as bridges for communications. Research on studying these communications on different platforms emerges during the meantime. Prior studies focus on areas such as topic modeling, sentiment analysis and prediction tasks such as predicting COVID-19 positive cases, misinformation spread, etc. However, online communications with media outlets remain unexplored on an international scale. We have little knowledge about the patterns of the media consumption geographically and their association with offline political preference. We believe addressing these questions could help governments and researchers better understand human behaviors during the pandemic. In this thesis, we specifically investigate the online consumption of media outlets on Twitter through a set of quantitative analyses. We make use of several public media outlet datasets to extract media consumption from tweets collected based on COVID-19 keyword matching. We make use of a metric "interaction" to quantify media consumption through weighted Twitter activities. We further construct a matrix based on it which could be directly used to measure user-media consumption in different granularities. We then conduct analyses on the United States level and global level. To the best of our knowledge, this thesis presents the first-of-its-kind study on media consumption on COVID-19 across countries, it sheds light on understanding how people consume media outlets during the pandemic and provides potential insights for peer researchers.

The Shapes of the Fourth Estate During the Pandemic: Profiling COVID-19 News Consumption in Eight Countries (preprint)

News media is often referred to as the Fourth Estate, a recognition of its political power. New understandings of how media shape political beliefs and influence collective behaviors are urgently needed in an era when public opinion polls do not necessarily reflect election results and users influence each other in real-time under algorithm-mediated content personalization. In this work, we measure not only the average but also the distribution of audience political leanings for different media across different countries. The methodological components of these new measures include a high-fidelity COVID-19 tweet dataset; high-precision user geolocation extraction; and user political leaning estimated from the within-country retweet networks involving local politicians. We focus on geolocated users from eight countries, profile user leaning distribution for each country, and analyze bridging users who have interactions across multiple countries. Except for France and Turkey, we observe consistent bi-modal user leaning distributions in the other six countries, and find that cross-country retweeting behaviors do not oscillate across the partisan divide. More importantly, this study contributes a new set of media bias estimates by averaging the leaning scores of users who share the URLs from media domains. Through two validations, we find that the new average audience leaning scores strongly correlate with existing media bias scores. Lastly, we profile the COVID-19 news consumption by examining the audience leaning distribution for top media in each country, and for selected media across all countries. Those analyses help answer questions such as: Does center media Reuters have a more balanced audience base than partisan media CNN in the US? Does far-right media Breitbart attract any left-leaning readers in any countries? Does CNN reach a more balanced audience base in the US than in the UK?

Spillover effects from news to travel and leisure stocks during the COVID-19 pandemic: Evidence from the time and frequency domains

The impact of the COVID-19 pandemic on tourism has received general attention in the literature, while the role of news during the pandemic has been ignored. Using a time-frequency connectedness approach, this paper focuses on the spillover effects of COVID-19-related news on the return and volatility of four regional travel and leisure (T&L) stocks. The results in the time domain reveal significant spillovers from news to T&L stocks. Specifically, in the return system, T&L stocks are mainly affected by media hype, while in the volatility system, they are mainly affected by panic sentiment. This paper also finds two risk contagion paths. The contagion index and Global T&L stock are the sources of these paths. The results in the frequency domain indicate that the shocks in the T&L industry are mainly driven by short-term fluctuations. The spillovers from news to T&L stocks and among these T&L stocks are stronger within 1 month.

Prevalence and risk factors of depression and anxiety among Chinese adults who received SARS-CoV-2 vaccine - A cross-sectional survey.

BACKGROUND: Direct data reflecting the psychological problems during the nationwide SARS-CoV-2 vaccination campaign are scarce in China. The aim of this study was to assess the prevalence of depression and anxiety and investigate the associated risk factors after vaccination against SARS-CoV-2 among Chinese adults. METHODS: We conducted a web-based cross-sectional survey from June to July 2021. A structured questionnaire including the Patient Health Questionnaire-9(PHQ-9) and Generalized Anxiety Disorder-7(GAD-7) was used to investigated depression and anxiety symptoms. After excluding 223 ineligible records, a total of 6984 participants were included in our final analysis. Multivariable logistic regression analysis was used to examined the potential factors associated with depression or anxiety. RESULTS: Our data indicated that the overall prevalence of depression and anxiety was assessed at 19.39 % and 9.74 %, respectively. Participants who had vaccinated the second dose were more likely to have depressive symptoms (20.95 % vs.16.40 %) and anxiety symptoms (10.38 % vs. 8.51 %) than who had vaccinated the first dose. Multivariable logistic regression analysis indicated female gender, being healthcare worker, college or above and planning a pregnancy were all independently linked to depression or anxiety. LIMITATIONS: The present study was based on an online survey. CONCLUSION: The present study confirmed the presence of depression and anxiety among Chinese adults who received SARS-COV-2 vaccine, as well as the potential influencing factors. Additional attention and psychological support should be directed at these high-risk groups during SARS-CoV-2 vaccination campaign.

Autistic traits and gender modulate emotion changes before and during the COVID-19 pandemic.

Individuals with autism spectrum disorder (ASD) show an enhanced response to stressors, and gender plays an important role in stress response. Thus, autistic traits (ATs) in the general population and gender may regulate the emotion changes before and during the COVID-19 pandemic. In the present study, participants were divided into higher and lower ATs groups. The generalized linear models were used to estimate the effects of the independent variables (e.g. the COVID-19 pandemic status (before, during), gender (male, female), and AT groups (higher ATs, lower ATs) and their interactions on emotions measured by the Positive and Negative Affect scales. The results showed that the COVID-19 pandemic reduced positive emotions and increased fear and anger. Furthermore, compared with the status before the COVID-19 pandemic, individuals with higher ATs and females experienced stronger anger and fear than individuals with lower ATs and males during the pandemic. The present study revealed the emotional impacts of the COVID-19 pandemic and greater emotional susceptibility to the pandemic among individuals with higher ATs and females. Our findings provide prospective evidence for understanding the ASD/ATs-related enhanced response to pathogen threat-related stressors and have implications for COVID-19 crisis interventions.