Everybody's measuring themselves less frequently. The CDC is sort of cutting back on its measurements. "The traditional data sources are getting worse. These days, the quality of COVID tracking has become a cause for concern for Beauchamp and other experts working with public health data, especially as President Joe Biden declared the pandemic "over". Why some believe the official data is a "big mess" Some researchers refer to these trends as "digital breadcrumbs," because online activity, like searches, interacting with old Twitter threads, or in this case, leaving a review, can give unique insight into a person's real life circumstances.Īs for Beauchamp, he maintains a healthy level of skepticism for the study, even with all of his controls. One interesting reaction Beauchamp observed was the tweets and the study itself have evolved into their own meta-data sets, gaining popularity again when users are noticing a surge in COVID cases. I presume the reviews themselves weren't changing very much," Beauchamp said. "That is either due to lack of measurement of COVID, or worse measurements of COVID, or maybe something else changing. In other words, the rise in negative reviews might actually be an earlier warning sign than the official COVID data. After adding more months of data to his model in June this year, he found that the relationship between the reviews and COVID rates had swapped again: the reviews were now predictive of COVID rates. Using the past COVID cases to predict future COVID cases is pretty good, and you can't really do any better using the reviews."īut then something happened. "The other thing that I was trying to find was, 'Can we predict COVID cases using the reviews?' And what we found was that at least up through December of 2021, not really. Ultimately, the results from the paper showed that COVID cases were predictive of the reviews, meaning that if there was a recorded surge in COVID cases, there would likely be an increase in the negative reviews. "It's a very small paper, but it's one that I think has caught a lot of people's interest, particularly because it's trying to do slightly more carefully something that a lot of people have been noticing qualitatively on Twitter," he said. By mid-January, he had written a paper and submitted it to a journal, and by June of this year it had been published. To his surprise, the relationship was clear COVID cases followed a very similar pattern to the frequency of the reviews.īeauchamp's initial tweets on the findings in December 2021 went viral as well, and he scrambled to add more data to find a definitive answer.
Maybe I'll just try scraping some Amazon reviews and see what the actual trends are, as opposed to just cutting and pasting a few reviews that mention a lack of smell," Beauchamp said. "I just thought, well, it's easy enough to do. And having focused on previous projects that attempted to predict COVID cases using social media data, he sought to create a model to test it. He decided it wouldn't be too difficult to find out if there was actually a link. Nick Beauchamp is an associate professor of political science at Northeastern University and first caught wind of the Yankee Candle theory late last year. That theory was put under the microscope, and has taken on new relevance amid concern at the lack of official data tracking infections across the U.S. After noticing this trend, people began to ask: could the reviews themselves be a reliable indicator of a surge in the virus? Losing your sense of smell is one of the more recognized symptoms of an infection. Whenever there was an influx of negative reviews citing no smell, there was usually a spike in COVID cases to go along with it. Over the course of the pandemic, social media sleuths, epidemiologists and health nerds alike began noticing an interesting trend in the review section for Yankee candles on Amazon.
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