activity
20202022
most citedText Mining of Stocktwits Data for Predicting Stock Prices

52 citations · 58 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20225 cited

Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model

Usman Naseem, Byoung Chan Lee, Matloob Khushi +2

A user-generated text on social media enables health workers to keep track of information, identify possible outbreaks, forecast disease trends, monitor emergency cases, and ascert…

cs.CL2021

Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT

Usman Naseem, Adam G. Dunn, Matloob Khushi +1

The availability of biomedical text data and advances in natural language processing (NLP) have made new applications in biomedical NLP possible. Language models trained or fine tu…

cs.CL2021

Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU

Usman Naseem, Matloob Khushi, Jinman Kim +1

Vaccines are an important public health measure, but vaccine hesitancy and refusal can create clusters of low vaccine coverage and reduce the effectiveness of vaccination programs.…

q-fin.ST202152 cited

Text Mining of Stocktwits Data for Predicting Stock Prices

Mukul Jaggi, Priyanka Mandal, Shreya Narang +2

Stock price prediction can be made more efficient by considering the price fluctuations and understanding the sentiments of people. A limited number of models understand financial…

cs.CL20201 cited

BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition

Usman Naseem, Matloob Khushi, Vinay Reddy +3

In recent years, with the growing amount of biomedical documents, coupled with advancement in natural language processing algorithms, the research on biomedical named entity recogn…