As the pandemic creeps up to its one year anniversary, the messages of social distancing, wearing masks, and flattening the curve have begrudgingly become accepted as part of our 2020 lexicon. But we know words are only part of the message -- how we feel will ultimately determine how we act.
Our team has been using the power of machine learning to read between the lines. Connected to policy directives and public health messages are emotional reactions that are hard to decipher. We are analysing thousands of tweets from online users who are responding to announcements from Canadian health organizations and officials. Across the country, we’ve seen responses to everything from travel restrictions, mask protocols, lockdown measures, and most recently the second wave of rising case counts.
What can these tweets, this data, tell us?
Emotions are inextricably linked to behaviour, inspiring our team to ask: How might we understand public reaction to policy directions and restrictions on social media and how can this feedback loop inform how we approach public health communications?
To begin to understand this complex space, our team has narrowed our focus on analysing the responses from the public to announcements by public health officials and organizations on Twitter.
We’ve seen our southern neighbours continue to struggle with the impacts of unchecked misinformation on social media, in large part driven by emotional and ideological responses to political leaders. As Canadians we are not immune to these forces but we recognize the issue, and use this as an opportunity to conduct “pulse checks” on public opinion and discourse throughout the pandemic.
We also know this analysis is one part of a larger story. These emotions speak to deeper systemic issues that must also be addressed. Our next blog takes an equity-lens to our work to understand the limitations and opportunities of social media platforms to impact structural change.
As we better understand how (mis)information can polarize nations, cripple democracies, and fuel the spread of disease, leaders must start asking: how can we build better mechanisms for effective communication and integrate better feedback loops for emotional reactions to inform decision making?
As researchers, we believe that what you can measure, you can then understand and attempt to influence.