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Welcome to another episode of Faster Than Normal! Happy that you’re here!

We’re talking this week with Lyle Ungar and Sharath Chandra Guntuku about their study: "Language of ADHD in Adults on Social Media".

Lyle is a Professor of Computer and Information Science at The University of Pennsylvania. His current research focuses on developing scalable machine learning methods for data mining and text mining,including deep learning methods for natural language processing, and analysis of social media to better understand the drivers of physical and mental well-being.

Sharath is a post-doctoral researcher in the Perelman School of Medicine and in the Department of Computer and Information Science at the University of Pennsylvania. Prior to joining Penn, he completed his PhD studies on building machine learning algorithms to model users’ personality in multimedia preferences at the School of Computer Science and Engineering at Nanyang Technological University in Singapore. His current research aims to leverage large-scale social media image and text data to model social health outcomes and psychological traits.

SHOW NOTES:

1:18 FitKit.com

2:17 Welcome and Introductions

3:18 How did you get the idea for the study “What can Twitter reveal about people with ADHD”?

4:18 Twitter, dopamine, posting and an immediate gratification connection?

5:17 Time condensing and ‘slow media’ among teens

6:34 Mood swings and possible self-regulating online? Language and nuances

8:09 Immediate feedback loops

9:05 Downtime. Typing with purpose. Condition-specific Apps?

10:20 Bombwords, double-check delay and e-tools

12:35 No mirriors yet in Social Media. Yet.

13:07 Many different types of ADHD and what Social Media can tell us

15:00 If the goal is to better understand the condition, then what’s next?

16:15 What some Social Media Research shows and will we see a shift once people with ADHD understand how to use it for Good?

18:00. How can we follow your research. the World Well Being Project www.WWBP.org

18:45. Thank you!

19:05 Outros