SPEED

Data for our NAACL-2024 paper "Event Detection from Social Media for Epidemic Prediction"

Owing to Twitter's data-sharing policy, we can't publicly share the data. But you can fill out this Google Form, and we can reach out to you with steps to procure the data.

Data Statistics

Here are some high level statistics of our data:

# Event Types	7
# Sentences	2,561
# Event Mentions	2,889
Average Event Mentions per Event	413

We also present the statistics for the train-dev-test splits of our data below:

Split	Disease	# Sentences	# Event Mentions
Train	COVID	1,601	1,746
Dev	COVID	374	471
Test	Mpox	286	398
Test	Zika/Dengue	300	274

Training/Evaluating Models

For all model training/evaluations, we utilize TextEE. Majorly we export our data as a dataset in this repo, create specific configs, and train/evaluate the models using the TextEE scripts.