5 citations · 5 across the 4 of their papers we have counts for
5 papers
Semi-Supervised Text Classification via Self-Pretraining
Payam Karisani, Negin Karisani
We present a neural semi-supervised learning model termed Self-Pretraining. Our model is inspired by the classic self-training algorithm. However, as opposed to self-training, Self…
View Distillation with Unlabeled Data for Extracting Adverse Drug Effects from User-Generated Data
Payam Karisani, Jinho D. Choi, Li Xiong
We present an algorithm based on multi-layer transformers for identifying Adverse Drug Reactions (ADR) in social media data. Our model relies on the properties of the problem and t…
Domain-Guided Task Decomposition with Self-Training for Detecting Personal Events in Social Media
Payam Karisani, Joyce C. Ho, Eugene Agichtein
Mining social media content for tasks such as detecting personal experiences or events, suffer from lexical sparsity, insufficient training data, and inventive lexicons. To reduce…
Mining Coronavirus (COVID-19) Posts in Social Media
Negin Karisani, Payam Karisani
World Health Organization (WHO) characterized the novel coronavirus (COVID-19) as a global pandemic on March 11th, 2020. Before this and in late January, more specifically on Janua…
Did You Really Just Have a Heart Attack? Towards Robust Detection of Personal Health Mentions in Social Media
Payam Karisani, Eugene Agichtein
Millions of users share their experiences on social media sites, such as Twitter, which in turn generate valuable data for public health monitoring, digital epidemiology, and other…