In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

[EX Q]: We collect three years of online news articles from June 2016 to June 2019. 
 Question: What unlabeled corpus did they use?
[EX A]: three years of online news articles from June 2016 to June 2019

[EX Q]:  News Articles
Our dataset source of news articles is described in BIBREF2. This dataset was built from two different sources, for the trusted news (real news) they sampled news articles from the English Gigaword corpus. For the false news, they collected articles from seven different unreliable news sites. Twitter
For this dataset, we rely on a list of several Twitter accounts for each type of false information from BIBREF6. This list was created based on public resources that annotated suspicious Twitter accounts. The authors in BIBREF6 have built a dataset by collecting tweets from these accounts and they made it available.  
 Question: What datasets did they use?
[EX A]: News Articles Twitter

[EX Q]: The baseline model for our experiments is explained in the paper by Alec Go [1]. The model uses the Naive Bayes, SVM, and the Maximum Entropy classifiers for their experiment. 
 Question: What previously proposed methods is this method compared against?
[EX A]:
Naive Bayes SVM Maximum Entropy classifiers