Thefirst tweetthat the UK’s Department of Health and Social Care published about its new coronavirus testing regime came on January 25 2020. Less than a week later, the departmenttweetedits first announcement of two positive tests for COVID-19 in the UK, foreshadowing achain of eventsthat would have a profound effect on people’s lives.
As the coronavirus spread, these initial tweets were joined by millions of others, as people reacted topanic buying, rumouredlockdownsand heart-wrenchingstoriesfrom across the world.
Soon, tweets about masks, the R number and herd immunity were competing with misinformation and conspiracy theories as the country “doomscrolled” through Twitter. Eventually, tweets about loo roll would be replaced by tweets about the rollout of vaccines worldwide – and the long-awaitedroadmapback to normality.
Taken together, these tweets are a sprawling historical document – a modern-daydiary of Samuel Pepys– revealing how life has changed during the pandemic. But with millions of tweets to sift through, making sense of them all requires careful archiving.
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My colleagues and I have performed this archiving, creating apublicly accessible databaseof pandemic-related tweets that anyone can access. We hope the archive will help researchers and the public make sense of all that’s changed since the early weeks of 2020.
Twitter as research tool
Twitter is already regularly used as a research tool. One particularly interestingstudyrevealed how early warning signs of COVID-19 spreading in Europe, signalled by an uptick in the use of words like “pneumonia”, were on Twitter as early as January 2020.
Our Twitter archive also shows how tweets mentioning ‘pneumonia’ increased long before March 2020. Author provided
In other work, researchers haveexaminedhow world leaders turned to Twitter during the pandemic, and others have createddatasetsto expose how the public perceived their COVID-19 policies. Anotherdataset, from the University of Southern California, contains 123 million tweets, covering English, French, Thai, Indonesian and more.
Then came studies of misinformation on Twitter, which has been a key concern since the start of the pandemic.One studyfound that completely false claims spread faster than tweets with partially false claims.Another studyfound that unverified personal Twitter accounts featured the highest rate of COVID-19 misinformation, and that hashtags like #ncov2019 were more likely to be used in misinformation tweets than #Covid19.
Misinformation has also led to the emergence of conspiracy theories. Investigation shows they claim the virus was developed asa biological weapon, that the vaccination programme is a front for amass surveillance programme, and even that the entire pandemicis a hoax.
These findings helped pressuresocial media companiesto ban persistent offenders,remove misinformation tweets,hire more fact checkers, andadd warningsto disputed information.
Archiving Twitter
As useful as all these studies are in capturing public opinion and encouraging platforms to moderate misinformation, most of their datasets are not publicly accessible and you need special skills to access and analyse them.
To address this barrier,our teamat Birmingham City University has developed the Trust and Communication: Coronavirus Online Visual Dashboard (TRAC:COVID). It’s a collection of over 84 million tweets in English that contain words and hashtags related to the pandemic. It currently covers UK tweets from January 2020 to April 2021, and will be extended as we acquire more data.
TRAC:COVID is built on methods from a discipline known as corpus linguistics, which uses software to research a large body of text, known as a corpus. A corpus can be any size, but many of the largest online corpora contain millions or even billions of words.
Corpus linguistics has recently been used to analyse healthcare communications, from work onNHS patient feedbackto understandingrepresentations of obesityin the British press.
One of the main benefits of corpus linguistics is that it helps us quickly analyse millions of words, allowing researchers to develop deeper insights compared to manual inspection.
Since our corpus covers a specific period, users can chart how language use changed during the pandemic, how particular words have acquired new meanings, or when certain words stop being used altogether – all without requiring specialist knowledge or language analysis skills. Pulling these different strands together, we can build a detailed timeline of how conversations about COVID-19 have changed.
Our archive reveals words associated with key terms like ‘lockdown’. TRAC:COVID
Reducing vaccine hesitancy
Our Twitter archive could also help us tackle ongoing issues related to the pandemic. Chief among them is vaccine hesitancy, whichstudies have shownto be fuelled by misinformation shared on platforms such as Twitter.
Using the TRAC:COVID archive, we’ve investigated vaccine-related tweets to get an idea of the scale and diversity of “anti-vax” stances on Twitter. While the most frequent hashtags were generally positive, such as #vaccineswork and #getvaccinated, we found several hashtags that spoke to different communities of anti-vaxxers.
The diagram below illustrates how these anti-vax discourses intersect with conspiracy theories and bunk science, exposing how anti-vaxxers are part of a broader constellation of fringe beliefs.
Using our archive, we can quickly identify anti-vaccine keywords. TRAC:COVID, Author provided
In extreme cases, these beliefs can cause widespreadmedical harm. For example, the UK has seen an increase in children contracting measles and mumps due to a growing number of parents choosing not to have their children vaccinated because of the fraudulent suggestion that the MMR vaccinecauses autism.
Tweets about COVID-19 represent an important cultural artefact, charting how conversations and concerns about the pandemic have shifted over time. With our new resource, people will be able to explore a giant archive of pandemic perspectives, deepening their understanding of what preoccupied UK Twitter users during a unique period of world history.
This article byRobert Lawson, Associate Professor in Sociolinguistics,Birmingham City Universityis republished fromThe Conversationunder a Creative Commons license. Read theoriginal article.
Story byThe Conversation
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