Matthew Matero
Stony Brook University
14 Papers
4 Citations
Matthew Matero is an academic researcher from Stony Brook University. The author has contributed to research in topics: Computer science & Task (project management). The author has an hindex of 2, co-authored 6 publications.
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Papers
Suicide Risk Assessment with Multi-level Dual-Context Language and BERT
Matthew Matero,Akash Idnani,Youngseo Son,Salvatore Giorgi,Huy Vu,Mohammadzaman Zamani,Parth Limbachiya,Sharath Chandra Guntuku,H. Andrew Schwartz +8 more
- 01 Jun 2019
TL;DR: This work uses dual context based approaches (modeling content from suicide forums separate from other content), built over both traditional ML models as well as a novel dual RNN architecture with user-factor adaptation to explore the use of open-vocabulary and theoretical features for suicide risk assessment on support forums.
122
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and Dimensionality.
Adithya V Ganesan,Matthew Matero,Aravind Reddy Ravula,Huy Vu,H. Andrew Schwartz +4 more
- 01 Jun 2021
TL;DR: A systematic study on the role of dimension reduction methods as well as the dimensionality of embedding vectors and sample sizes as a function of predictive performance finds that fine-tuning large models with a limited amount of data pose a significant difficulty which can be overcome with a pre-trained dimension reduction regime.
•Posted Content
MeLT: Message-Level Transformer with Masked Document Representations as Pre-Training for Stance Detection
TL;DR: This article proposed a Message-Level Transformer (MeLT) model, which is a hierarchical message-encoder pre-trained over Twitter and applied to the task of stance prediction.
13
Using Facebook language to predict and describe excessive alcohol use.
Rupa Jose,Matthew Matero,Garrick Sherman,Brenda Curtis,Sal Giorgi,H. Andrew Schwartz,Lyle H. Ungar +6 more
TL;DR: The use of social media data to study drinking behavior in the general public is promising and could eventually support primary and secondary prevention efforts among Americans whose at-risk drinking may have otherwise gone "under the radar."
10
Opioid death projections with AI-based forecasts using social media language
TL;DR: T r OP as discussed by the authors is a model for community-specific trend projection that uses community specific social media language along with past opioid-related mortality data to predict future changes in opioidrelated deaths.