Researchers have trained a machine-learning algorithm to analyze a massive number of tweets about climate change and vaccination.

Researchers found that climate change sentiment was overwhelmingly on the pro side of those that believe climate change is because of human activity and requires action. There was also a significant amount of interaction between users with opposite sentiments about climate change.
However, in the snapshot of the timeframe of the dataset, vaccine sentiment was nowhere near so uniform. Only some 15 or 20 percent of users expressed a pro-vaccine sentiment, while around 70 percent expressed no strong sentiment.
Perhaps more importantly, individuals and entire online communities with differing sentiments toward vaccination interacted much less than the climate change debate.
“It is an open question whether these differences in user sentiment and social media echo chambers concerning vaccines created the conditions for highly polarized vaccine sentiment when the COVID-19 vaccines began to roll out,” said Chris Bauch, professor of applied mathematics at the University of Waterloo.
The research goal was to learn how sentiments on climate change and vaccination may be related, how users form networks and share information, the relationship between online sentiments, and how people act and make decisions in daily life.
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The dataset for the project was drawn from a few sources, including some that were purchased from Twitter. In total, the analysis takes into consideration roughly 87 million tweets. The time range for the tweets is between 2007 and 2016.
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The AI ranked the millions of tweets as either pro, anti or neutral sentiment on the issues and then classified users in pro, anti or neutral categories. It also analyzed the structure of online communities and the degree to which users with opposing sentiments interacted.
Source-Medindia