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Dealing with a global pandemic has affected the mental health of millions of people. A team of researchers from MIT and Harvard University has shown that they can measure these effects by analyzing the language people use to express their fear online.
Using machine learning to analyze the text of more than 800,000 Reddit posts, the researchers were able to identify changes in the tone and content of the language used as the first wave of the Covid-19 pandemic from January to April 2020. analysis revealed several important changes in mental health conversations, including an overall increase in discussion of anxiety and suicide.
“We found that there were these natural clusters that arose in connection with suicide and loneliness, and the number of jobs in these clusters more than doubled during the pandemic compared to the same months last year, which is Serious Problem, ”says Daniel Low, a graduate student in the languages and life sciences hearing and technology program at Harvard and MIT, and lead author of the study.
The analysis also found different effects on people already suffering from different types of mental illness. The findings could help psychiatrists, or potential moderators of the Reddit forums studied, better identify and help people whose mental health suffers, the researchers say.
“When the mental health needs of so many people in our society are inadequately met, even at the beginning of their studies, we wanted to draw attention to the ways many people suffer during this period in order to strengthen and inform allocating resources, to support them. “”, Says Laurie Rumker, a PhD candidate in the PhD program in bioinformatics and integrative genomics at Harvard and one of the authors of the study.
Satrajit Ghosh, senior scientist at MIT’s McGovern Institute for Brain Research, is the lead author of the study, which appears in the Journal of Internet Medical Research. Other authors of the paper include Tanya Talkar, a PhD student in the Language and Hearing Biosciences and Technology program at Harvard and MIT; John Torous, director of the digital psychiatry division at Beth Israel Deaconess Medical Center; and Guillermo Cecchi, principal investigator at the IBM Thomas J. Watson Research Center.
A wave of fear
The new study originated from the MIT 6.897 / HST.956 (Machine Learning for Healthcare) class at the MIT Institute for Electrical Engineering and Computer Science. Low, Rumker, and Talkar, who took the course last spring, had already done some research on using machine learning to identify mental disorders based on how people talk and what they say. After the start of the Covid-19 pandemic, they decided to focus their class project on analyzing Reddit forums that deal with different types of mental illness.
“When Covid arrived, we were all curious to know if it affected some communities more than others,” Low says. “Reddit gives us the ability to view all of these subreddits, which are specialized support groups, in real time. It’s a truly unique opportunity to see how these different communities were affected differently during the wave.”
The researchers analyzed contributions from 15 subreddit groups addressing a variety of mental illnesses, including schizophrenia, depression and bipolar disorder. This included a handful of groups dealing with issues not specifically related to mental health, such as: B. Personal finance, fitness and parenting.
Using various types of natural language processing algorithms, the researchers measured the frequency of words associated with topics such as fear, death, isolation and substance abuse, and grouped posts based on similarities in the language used. These approaches allowed the researchers to identify similarities between posts in each group after the outbreak of the pandemic, as well as significant differences between the groups.
The researchers found that while most members of the support groups began publishing Covid-19 in March, the group that dealt with health anxiety started much earlier in January. However, as the pandemic progressed, the other mental health groups looked very similar to the health fear group in terms of the more common language used. At the same time, the personal finance group showed the most negative semantic shift from January to April 2020, greatly increasing the use of words related to economic stress and negative mood.
They also found that the mental health groups most affected at the start of the pandemic were those linked to ADHD and eating disorders. Researchers have speculated that people suffering from these disorders will find it much more difficult to cope with their condition due to blockages without their usual social support systems. In these groups, the researchers found posts on news hyperfocusing and fallout
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