1 code implementation • LREC 2022 • Ayah Zirikly, Bart Desmet, Julia Porcino, Jonathan Camacho Maldonado, Pei-Shu Ho, Rafael Jimenez Silva, Maryanne Sacco
Whole-person functional limitations in the areas of mobility, self-care and domestic life affect a majority of individuals with disabilities.
no code implementations • NAACL (CLPsych) 2022 • Adam Tsakalidis, Jenny Chim, Iman Munire Bilal, Ayah Zirikly, Dana Atzil-Slonim, Federico Nanni, Philip Resnik, Manas Gaur, Kaushik Roy, Becky Inkster, Jeff Leintz, Maria Liakata
We provide an overview of the CLPsych 2022 Shared Task, which focusses on the automatic identification of ‘Moments of Change’ in lon- gitudinal posts by individuals on social media and its connection with information regarding mental health .
no code implementations • NAACL (CLPsych) 2022 • Ayah Zirikly, Mark Dredze
In the case of mental health diagnosis, clinicians already rely on an assessment framework to make these decisions; that framework can help a model generate meaningful explanations. In this work we propose to use PHQ-9 categories as an auxiliary task to explaining a social media based model of depression.
1 code implementation • ACL 2022 • Thong Nguyen, Andrew Yates, Ayah Zirikly, Bart Desmet, Arman Cohan
In dataset-transfer experiments on three social media datasets, we find that grounding the model in PHQ9's symptoms substantially improves its ability to generalize to out-of-distribution data compared to a standard BERT-based approach.
1 code implementation • ICLR 2021 • Joshua C. Chang, Patrick Fletcher, Jungmin Han, Ted L. Chang, Shashaank Vattikuti, Bart Desmet, Ayah Zirikly, Carson C. Chow
However, sparsity in representation decoding does not necessarily imply sparsity in the encoding of representations from the original data features.
no code implementations • LREC 2020 • Bart Desmet, Julia Porcino, Ayah Zirikly, Denis Newman-Griffis, Guy Divita, Elizabeth Rasch
The disability benefits programs administered by the US Social Security Administration (SSA) receive between 2 and 3 million new applications each year.
no code implementations • WS 2019 • Denis Newman-Griffis, Ayah Zirikly, Guy Divita, Bart Desmet
Finally, we highlight several challenges in classifying performance assertions, including capturing information about sources of assistance, incorporating syntactic structure and negation scope, and handling new modalities at test time.
no code implementations • WS 2019 • Ayah Zirikly, Philip Resnik, {\"O}zlem Uzuner, Kristy Hollingshead
The shared task for the 2019 Workshop on Computational Linguistics and Clinical Psychology (CLPsych{'}19) introduced an assessment of suicide risk based on social media postings, using data from Reddit to identify users at no, low, moderate, or severe risk.
no code implementations • WS 2018 • Sean MacAvaney, Bart Desmet, Arman Cohan, Luca Soldaini, Andrew Yates, Ayah Zirikly, Nazli Goharian
Self-reported diagnosis statements have been widely employed in studying language related to mental health in social media.
1 code implementation • WS 2018 • Denis Newman-Griffis, Ayah Zirikly
Functioning is gaining recognition as an important indicator of global health, but remains under-studied in medical natural language processing research.
no code implementations • WS 2018 • Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daum{\'e} III, Philip Resnik
We report on the creation of a dataset for studying assessment of suicide risk via online postings in Reddit.
no code implementations • WS 2016 • Ayah Zirikly, Bart Desmet, Mona Diab
This paper describes the GW/LT3 contribution to the 2016 VarDial shared task on the identification of similar languages (task 1) and Arabic dialects (task 2).
no code implementations • WS 2016 • Mohammed Attia, Ayah Zirikly, Mona Diab
The interaction between roots and patterns in Arabic has intrigued lexicographers and morphologists for centuries.