New AI Tool Tracks Evolution of COVID-19 Conspiracy Theories on Social Media

A new machine-learning program accurately identifies COVID-19-related conspiracy theories on social media and models how they evolved over time - a tool that could someday help public health officials combat misinformation online.

"A lot of machine-learning studies related to misinformation on social media focus on identifying different kinds of conspiracy theories," said Courtney Shelley, a postdoctoral researcher in the Information Systems and Modeling Group at Los Alamos National Laboratory and co-author of the study that was published last week in the Journal of Medical Internet Research. "Instead, we wanted to create a more cohesive understanding of how misinformation changes as it spreads. Because people tend to believe the first message they encounter, public health officials could someday monitor which conspiracy theories are gaining traction on social media and craft factual public information campaigns to preempt widespread acceptance of falsehoods."

The study, titled "Thought I'd Share First," used publicly available, anonymized Twitter data to characterize four COVID-19 conspiracy theory themes and provide context for each through the first five months of the pandemic. The four themes the study examined were that 5G cell towers spread the virus; that the Bill and Melinda Gates Foundation engineered or has otherwise malicious intent related to COVID-19; that the virus was bioengineered or was developed in a laboratory; and that the COVID-19 vaccines, which were then all still in development, would be dangerous.

"We began with a dataset of approximately 1.8 million tweets that contained COVID-19 keywords or were from health-related Twitter accounts," said Dax Gerts, a computer scientist also in Los Alamos' Information Systems and Modeling Group and the study's co-author. "From this body of data, we identified subsets that matched the four conspiracy theories using pattern filtering, and hand labeled several hundred tweets in each conspiracy theory category to construct training sets."

Using the data collected for each of the four theories, the team built random forest machine-learning, or artificial intelligence (AI), models that categorized tweets as COVID-19 misinformation or not.

"This allowed us to observe the way individuals talk about these conspiracy theories on social media, and observe changes over time," said Gerts.

The study showed that misinformation tweets contain more negative sentiment when compared to factual tweets and that conspiracy theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events.

For example, Bill Gates participated in a Reddit "Ask Me Anything" in March 2020, which highlighted Gates-funded research to develop injectable invisible ink that could be used to record vaccinations. Immediately after, there was an increase in the prominence of words associated with vaccine-averse conspiracy theories suggesting the COVID-19 vaccine would secretly microchip individuals for population control.

Furthermore, the study found that a supervised learning technique could be used to automatically identify conspiracy theories, and that an unsupervised learning approach (dynamic topic modeling) could be used to explore changes in word importance among topics within each theory.

"It's important for public health officials to know how conspiracy theories are evolving and gaining traction over time," said Shelley. "If not, they run the risk of inadvertently publicizing conspiracy theories that might otherwise 'die on the vine.' So, knowing how conspiracy theories are changing and perhaps incorporating other theories or real-world events is important when strategizing how to counter them with factual public information campaigns."

Gerts D, Shelley CD, Parikh N, Pitts T, Watson Ross C, Fairchild G, Vaquera Chavez NY, Daughton AR.
"Thought I'd Share First" and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study.
JMIR Public Health Surveill. 2021. doi: 10.2196/26527

Most Popular Now

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

New AI Tool Illuminates "Dark Side…

Proteins sustain life as we know it, serving many important structural and functional roles throughout the body. But these large molecules have cast a long shadow over a smaller subclass...

Deep Learning-Based Model Enables Fast a…

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for definitive diagnosis. However, conventional...