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AI model detects mental disorders based on web posts
https://techxplore.com ^ | March 2,2022 | by Harini Barath, Dartmouth College

Posted on 03/03/2022 12:38:48 PM PST by Red Badger

Dartmouth researchers have built an artificial intelligence model for detecting mental disorders using conversations on Reddit, part of an emerging wave of screening tools that use computers to analyze social media posts and gain an insight into people's mental states.

What sets the new model apart is a focus on the emotions rather than the specific content of the social media texts being analyzed. In a paper presented at the 20th International Conference on Web Intelligence and Intelligent Agent Technology, the researchers show that this approach performs better over time, irrespective of the topics discussed in the posts.

There are many reasons why people don't seek help for mental health disorders—stigma, high costs, and lack of access to services are some common barriers. There is also a tendency to minimize signs of mental disorders or conflate them with stress, says Xiaobo Guo, Guarini '24, a co-author of the paper. It's possible that they will seek help with some prompting, he says, and that's where digital screening tools can make a difference.

"Social media offers an easy way to tap into people's behaviors," says Guo. The data is voluntary and public, published for others to read, he says.

Reddit, which offers a massive network of user forums, was their platform of choice because it has nearly half a billion active users who discuss a wide range of topics. The posts and comments are publicly available, and the researchers could collect data dating back to 2011.

In their study, the researchers focused on what they call emotional disorders—major depressive, anxiety, and bipolar disorders—which are characterized by distinct emotional patterns. They looked at data from users who had self-reported as having one of these disorders and from users without any known mental disorders.

They trained their model to label the emotions expressed in users' posts and map the emotional transitions between different posts, so a post could be labeled "joy," "anger," "sadness," "fear," "no emotion," or a combination of these. The map is a matrix that would show how likely it was that a user went from any one state to another, such as from anger to a neutral state of no emotion.

Different emotional disorders have their own signature patterns of emotional transitions. By creating an emotional "fingerprint" for a user and comparing it to established signatures of emotional disorders, the model can detect them. To validate their results, they tested it on posts that were not used during training and show that the model accurately predicts which users may or may not have one of these disorders.

This approach sidesteps an important problem called "information leakage" that typical screening tools run into, says Soroush Vosoughi, assistant professor of computer science and another co-author. Other models are built around scrutinizing and relying on the content of the text, he says, and while the models show high performance, they can also be misleading.

For instance, if a model learns to correlate "COVID" with "sadness" or "anxiety," Vosoughi explains, it will naturally assume that a scientist studying and posting (quite dispassionately) about COVID-19 is suffering from depression or anxiety. On the other hand, the new model only zeroes in on the emotion and learns nothing about the particular topic or event described in the posts.

While the researchers don't look at intervention strategies, they hope this work can point the way to prevention. In their paper, they make a strong case for more thoughtful scrutiny of models based on social media data. "It's very important to have models that perform well," says Vosoughi, "but also really understand their working, biases, and limitations."

Explore further

Can emoji use be the key in detecting remote-work burnout?

More information:

Xiaobo Guo, Yaojia Sun, Soroush Vosoughi, Emotion-based Modeling of Mental Disorders on Social Media. arXiv:2201.09451v1 [cs.SI], arxiv.org/pdf/2201.09451.pdf


TOPICS: Business/Economy; Computers/Internet; Conspiracy; Society
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To: Georgia Girl 2
Who tells AI what comments are mental?

God hating leftists, silly.

21 posted on 03/03/2022 12:52:59 PM PST by ecomcon
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To: Red Badger
AI model detects mental disorders based on web posts

Well don't let it loose on us!

22 posted on 03/03/2022 12:55:18 PM PST by DiogenesLamp ("of parents owing allegiance to no other sovereignty.")
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To: DiogenesLamp

If they give it a FB account it will go nuts.................


23 posted on 03/03/2022 12:56:34 PM PST by Red Badger (Homeless veterans camp in the streets while illegal aliens are put up in hotels.....................)
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To: Red Badger

Pure horseshyt. The DSM4 is political garbage and any computer program to detect non-existent disorders is garbage too.


24 posted on 03/03/2022 12:56:53 PM PST by Seruzawa ("The Political left is the Garden of Eden of incompetence" - Marx the Smarter (Groucho))
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To: Red Badger

:)


25 posted on 03/03/2022 12:57:09 PM PST by DiogenesLamp ("of parents owing allegiance to no other sovereignty.")
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To: Red Badger

Reddit is definitely the place to look for mental disorders.


26 posted on 03/03/2022 1:00:28 PM PST by Yashcheritsiy (I'd rather have one king 3000 miles away that 3000 kings one mile away)
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To: V_TWIN

And then respond to the AI’s finding.


27 posted on 03/03/2022 1:00:36 PM PST by HollyB
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To: Eccl 10:2

Will the AI analyze the content of our posts on FR to determine we are crazy?

Or will it just correlate posting on FR with insanity?


28 posted on 03/03/2022 1:01:59 PM PST by DannyTN
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To: Red Badger
Be assured that the AI algorithm will flag pro Trump, Christian or America 1st Americans as mentally deficient.
29 posted on 03/03/2022 1:02:14 PM PST by JesusIsLord
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To: Red Badger

Since liberalism is a mental disorder...


30 posted on 03/03/2022 1:03:03 PM PST by JimRed (TERM LIMITS, NOW! Militia to the border! TRUTH is the new HATE SPEECH.)
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To: Red Badger

Studying what comes out in writing from Dartmouth to academe and to its alumni, one can see with sadness that the campus fell deep into the narrow confines of being asleep at the wheel - known by the paradoxical, cynical, double speak adjective, “woke”! This “research” fails to peed behind rthe realities of today’s hugely censorious, one-sided, politicized, propaganda-driven online world.


31 posted on 03/03/2022 1:05:11 PM PST by Seeing More Clearly Now ( )
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To: Red Badger

COULD THIS EMOTIONLESS CONTENT BE FLAGGED AS AN EMOTIONAL RESPONSE????!!!! :( :(


32 posted on 03/03/2022 1:05:11 PM PST by rightwingcrazy (;-,)
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To: Red Badger

I would love to turn that loose on my web posts just see how whacked it thinks I am!


33 posted on 03/03/2022 1:05:12 PM PST by Little Ray (Civilization runs on a narrow margin. What sustains it is not magic, but hard work. )
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To: Red Badger

Field day on FR!!!


34 posted on 03/03/2022 1:05:42 PM PST by PIF (They came for me and mine ... now its your turn)
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To: Red Badger

LOL...Putinistas are going to have a melt down!


35 posted on 03/03/2022 1:08:16 PM PST by rrrod (6)
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To: Red Badger

Did they test it on Biden?


36 posted on 03/03/2022 1:08:17 PM PST by kanawa ((Securing the 2022/2024 elections is of paramount importance.))
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To: Red Badger

Part of the “social credit” system, I imagine.


37 posted on 03/03/2022 1:09:02 PM PST by BradyLS (DO NOT FEED THE BEARS!)
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To: Red Badger

LOL wonder what they would make of. a photo of a rabbit’s with a pancake on its head or dozens of post with one word,”Thailand”


38 posted on 03/03/2022 1:11:36 PM PST by mware (RETIRED)
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To: Red Badger

90% of AI is BS. 100% of computer models are BS. Put them together in an “AI model” and you get something that works? And it won’t simply confirm the biases of the developer like every other computer model?


39 posted on 03/03/2022 1:12:44 PM PST by ArcadeQuarters (Remember the 2020 backstabbers. No more RINOs ever!)
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To: Red Badger

It’s been great knowing you guys. I’m going to shut up now.


40 posted on 03/03/2022 1:14:57 PM PST by bk1000 (Banned from Breitbart)
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