Headlines dataset

Introduced by Misra et al. in Sarcasm Detection using Hybrid Neural Network

The Headlines dataset for sarcasm detection is collected from two news website. TheOnion aims at producing sarcastic versions of current events. The dataset includes all the headlines from News in Brief and News in Photos categories (which are sarcastic) and real (and non-sarcastic) news headlines from HuffPost. This dataset has following advantages over the existing Twitter datasets:

  • Since news headlines are written by professionals in a formal manner, there are no spelling mistakes and informal usage. This reduces the sparsity and also increases the chance of finding pre-trained embeddings.
  • Furthermore, since the sole purpose of TheOnion is to publish sarcastic news, the dataset has high-quality labels with much less noise as compared to Twitter datasets.
  • Unlike tweets which are replies to other tweets, the obtained news headlines are self-contained.
Source: https://github.com/rishabhmisra/News-Headlines-Dataset-For-Sarcasm-Detection


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