@inproceedings{77853997fd3b475e8047a55fa8b5080f,
title = "Exploring transformers and time lag features for predicting changes in mood over time",
abstract = "This paper presents transformer-based models created for the CLPsych 2022 shared task. Using posts from Reddit users over a period of time, we aim to predict changes in mood from post to post. We test models that preserve timeline information through explicit ordering of posts as well as those that do not order posts but preserve features on the length of time between a user{\textquoteright}s posts. We find that a model with temporal information may provide slight benefits over the same model without such information, although a RoBERTa transformer model provides enough information to make similar predictions without custom-encoded time information.",
author = "John Culnan and {Romero Diaz}, {Damian Y.} and Steven Bethard",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 8th Workshop on Computational Linguistics and Clinical Psychology, CLPsych 2022 ; Conference date: 15-07-2022",
year = "2022",
doi = "10.18653/v1/2022.clpsych-1.21",
language = "English (US)",
series = "CLPsych 2022 - 8th Workshop on Computational Linguistics and Clinical Psychology, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "226--231",
editor = "Ayah Zirikly and Dana Atzil-Slonim and Maria Liakata and Steven Bedrick and Bart Desmet and Molly Ireland and Andrew Lee and Sean MacAvaney and Matthew Purver and Rebecca Resnik and Andrew Yates",
booktitle = "CLPsych 2022 - 8th Workshop on Computational Linguistics and Clinical Psychology, Proceedings",
}