COVID-CQ

Published: 30 October 2020| Version 3 | DOI: 10.17632/38nyzyt9bz.3
Contributors:
Ece Mutlu, Toktam Oghaz, Jasser Jasser, Ege Tutunculer, Amirarsalan Rajabi, Aida Tayebi, Ozlem Ozmen, Ivan Garibay

Description

We report on the preparation of a stance data set, called COVID-CQ, for user-generated content on Twitter in the context of the COVID-19 pandemic. Particularly, we investigated more than 14 thousand tweets and annotated the opinions of the tweet initiators regarding the use of "Chloroquine" and "Hydroxychloroquine" for the treatment or prevention of the coronavirus. In our annotation procedure, each annotator was asked to annotate the individual tweets as "Against", "Favor" or "Neutral/None" for the unproven claim of "Cchloroquine/hydroxychloroquine is a cure for the novel coronavirus". We are aware that some of the tweets are removed from Twitter. If you want to access those deleted tweet items and/or have any trouble related to hydrating, feel free to reach out to us. Email addresses: ece.mutlu@ucf.edu, Toktam.Oghaz@ucf.edu, Jasser.Jasser@ucf.edu

Files

Categories

Artificial Intelligence, Machine Learning, Social Network Analysis, Social Networks, Twitter, COVID-19

Licence