Understanding Stay-at-home Attitudes through Framing Analysis of Tweets

TL;DR

This study analyzes Twitter posts during early COVID-19 to understand public attitudes towards stay-at-home orders, revealing how moral framing influences support or opposition and how these attitudes evolved over time.

Contribution

It introduces a dataset of annotated stay-at-home tweets and classifiers to analyze moral framing and attitude dynamics on social media during the pandemic.

Findings

Support was linked to care frames.

Opposition was linked to freedom and oppression frames.

Public resistance increased over time, reflecting political divisions.

Abstract

With the onset of the COVID-19 pandemic, a number of public policy measures have been developed to curb the spread of the virus. However, little is known about the attitudes towards stay-at-home orders expressed on social media despite the fact that social media are central platforms for expressing and debating personal attitudes. To address this gap, we analyze the prevalence and framing of attitudes towards stay-at-home policies, as expressed on Twitter in the early months of the pandemic. We focus on three aspects of tweets: whether they contain an attitude towards stay-at-home measures, whether the attitude was for or against, and the moral justification for the attitude, if any. We collect and annotate a dataset of stay-at-home tweets and create classifiers that enable large-scale analysis of the relationship between moral frames and stay-at-home attitudes and their temporal evolution. Our findings suggest that frames of care are correlated with a supportive stance, whereas freedom and oppression signify an attitude against stay-at-home directives. There was widespread support for stay-at-home orders in the early weeks of lockdowns, followed by increased resistance toward the end of May and the beginning of June 2020. The resistance was associated with moral judgment that mapped to political divisions.