WIE Invited Talk


We are pleased to announce the invited talk entitled "NLP Applications in Mental Health" by Dr. Nazli Goharian.    
The event is free and will be hosted on Zoom on Jun 7, 2022, at 11:00am - 12:00pm.  

  Date and Time




  • Date: 07 Jun 2022
  • Time: 11:00 AM to 12:00 PM
  • All times are (UTC-05:00) Eastern Time (US & Canada)
  • Add_To_Calendar_icon Add Event to Calendar
  • Starts 19 May 2022 06:53 PM
  • Ends 07 June 2022 11:00 AM
  • All times are (UTC-05:00) Eastern Time (US & Canada)
  • No Admission Charge


Dr. Nazli Goharian Dr. Nazli Goharian


NLP Applications in Mental Health

With the ever-increasing usage of social media to either explicitly seek help or to simply share thoughts and feelings, we, in the computational disciplines, have the opportunity to utilize such data for building datasets, models, and doing analysis.  I will share our collaborative work done at the Information Retrieval Lab at Georgetown University on detecting mental health concerns in social media posts. The first application is on a dedicated mental health forum where the users who register to share and communicate their thoughts and feelings are suffering from some sort of mental distress (sadness, depression, potential of self-harm, ….). The task is to triage the severity of users’ posts to detect early the potential of self-harm as well as to evaluate the impact of forum activities and conversations on the users during a period of time. In the second type of platform, i.e., non-dedicated, I focus on the question of whether we can detect if a user is suffering from any one or more of nine mental health conditions, only using the *general language* of the user; that is, the posts are not in mental health [sub]forums nor have any mental health related words. To address this question, we had to construct large scale datasets; I will explain how we have identified the diagnosed users, and how carefully selected the controls.  Further I will show the results of several baselines to detect the conditions. Identifying whether a given mental health condition of a user is a recent condition, similarly, whether the user currently suffers from a condition, are important questions yet challenging tasks as our efforts have shown us.  Detecting mental health conditions based on a relatively smaller number of posts generally is not promising; hence it is important to mitigate our approaches so that such low resource users do not go undetected. Finally, to address information reduction for a faster read and processing of users’ posts by moderators/counselors, I will provide our effort to summarize the posts to their short forms.


Nazli Goharian is Clinical Professor of Computer Science and Associate Director of the Information Retrieval Lab at Georgetown University, which she co-founded in 2010. She joined the Illinois Institute of Technology (IIT) from industry in 2000. Her research and doctoral student mentorship span the domains of information retrieval, text mining, and natural language processing. Specifically, her interest lies in humane-computing applications such as medical/health domain. Joint with her doctoral students, she received an EMNLP 2017 Best Long Paper Award and COLING 2018 Honorable Mention both for papers on mental health and social media.  For contributions to undergraduate and graduate curriculum development and teaching excellence, she was recognized with the IIT Julia Beveridge Award for faculty (university-wide female faculty of the year) in 2009, the College of Science and Letters Dean’s Excellence Award in Teaching in 2005, and in 2002, 2003, and 2007, the Computer Science Department Teacher of the Year Award.  She served as Senior/Area Chairs at ACL 2018, ACL 2019, ACL 2020 and ACL 2021.  She is co-chair of SIGIR Women in Information retrieval (WIR) since 2019, focusing on gender pay inequity and women leadership.