This directory contains two files containing ID's and labels for expriments conducted in our paper
"Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter".

The two files are:
* multiclass_tweets.csv
    - CSV containing ID's and four labels for the multiclass experiments 
    presented in the paper
    - The mapping between integers and labels in this dataset is the following:
    
    Propaganda: 0
    Clickbait: 1
    Satire: 2
    Hoax: 3

* binary_tweets.csv
    - CSV containing ID's and two labels for binary experiments
    presented in the paper
    - Note that the tweets labeled as 'unverified' in this dataset make up
    the dataset in multiclass.csv, but contain more granular labels in the multiclass.csv file
    - The mapping between integers and labels in this dataset is the following:
    
    Verified News: 0
    Unverified News: 1

Each of these contains the following columns:
* user_id: Twitter-assigned user ID
* tweet_id: Twitter-assigned tweet ID
* label: Integer indicating the label of tweets used in running our experiments for the paper
