Can social media data be used to evaluate the risk of human interactions during the COVID-19 pandemic?

Abstract

The United States has taken multiple measures to contain the spread of COVID-19, including the implementation of lockdown orders and social distancing practices. Evaluating social distancing is critical since it reflects the frequency of close human interactions. While questionnaire surveys or mobility data-based systems have provided valuable insights, social media data can contribute as an additional instrument to help monitor the risk of human interactions during the pandemic. For this reason, this study introduced a social media-based approach that quantifies the pro/anti-lockdown ratio as an indicator of the risk of human interactions. With the aid of natural language processing and machine learning techniques, this study classified the lockdown-related tweets and quantified the pro/anti-lockdown ratio for each state over time. The anti-lockdown ratio showed a moderate and negative correlation with the state-level social distancing index on a weekly basis, suggesting that people are more likely to travel out of the state where the higher anti-lockdown level is observed. The study further showed that the perception expressed on social media could reflect people’s behaviors. The findings of the study are of significance for government agencies to assess the risk of close human interactions and to evaluate their policy effectiveness in the context of social distancing and lockdown.

From science to politics: COVID-19 information fatigue on YouTube

“…The public’s perception of crises can be shaped by media content [ 13 , 35 , 51 , 52 ], as can behavioral responses [ 10 , 13 ]. Fatigue might contribute to behavior changes [ 45 , 46 ] (e.g., becoming less alert and paying less attention to distancing measures) and influence epidemic dynamics, especially when messages about controlling spread become less clear and more political [ 29 ].…”

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Flatten the curve: Empirical evidence on how non-pharmaceutical interventions substituted pharmaceutical treatments during COVID-19 pandemic

“…In this case, we plan to utilize social media data such as Facebook, Twitter, Instagram and so on as input to our model to capture people’s changing in the risk perception. Several studies have utilized social media data to extract people’s perception on COVID-19 related incidents like travelling [ 38 ], lockdown [ 39 ] and risk mitigation strategies [ 40 ].…”

A Systematic Review of Social Media and Government in the Social Science Discipline

“…This makes the country an intriguing case study (Liu, Tu, & Zhou, 2022;Meng, 2021). In addition, it has been suggested that nations that do not have robust democratic institutions may find that the platforms provided by social media might act as substitutes for platforms that allow for involvement and accountability (Li, Ma, Lee, & Lee, 2021). In this case, the Chinese fusion of the following things in general makes China a relevant point in this case on the issue of communication (Li et al, 2021;Zhang, Huang, & Liu, 2022).…”