Data Science for COVID-19 (DS4C)
The DS4C dataset is a structured collection of COVID-19 data from South Korea, based on reports from the Korea Centers for Disease Control & Prevention (KCDC) and local governments. It includes information on infections, patient routes, and various analyses. The dataset has been used for multiple research and visualization projects.
Nákvæm kynning
The Data Science for COVID-19 (DS4C) project provides a comprehensive dataset for analyzing the COVID-19 pandemic in South Korea. The dataset includes detailed information on infections, patient routes, and other relevant data. It has been used for various research and visualization projects, including competitions and academic studies. The data is sourced from the KCDC and local governments, ensuring accuracy and reliability.
MeiraGagnasett
t4d: Conversion Algorithm from ToMi to T4D Dataset
This project implements the conversion algorithm from the ToMi dataset to the T4D (Thinking is for Doing) dataset, as introduced in the paper https://arxiv.org/abs/2310.03051. It filters examples with Theory of Mind (ToM) questions and adapts the algorithm to account for second-order false beliefs.
Depression: Twitter Dataset + Feature Extraction
This dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.
Collaborative Assessment Dataset
Collaborative assessment as an intervention in the treatment of mental Illness: a systematic review