  Past studies in Sarcasm Detection mostly make use of Twitter datasets
collected using hashtag-based supervision but such datasets are noisy in terms
of labels and language. Furthermore, many tweets are replies to other tweets,
and detecting sarcasm in these requires the availability of contextual tweets.
To overcome the limitations related to noise in Twitter datasets, we curate
News Headlines Dataset from two news websites: TheOnion aims at producing
sarcastic versions of current events, whereas HuffPost publishes real news. The
dataset contains about 28K headlines out of which 13K are sarcastic. To make it
more useful, we have included the source links of the news articles so that
more data can be extracted as needed. In this paper, we describe various
details about the dataset and potential use cases apart from Sarcasm Detection.
