dataset_info:
features:
- name: text
dtype: string
- name: author
dtype: string
- name: score
dtype: int64
- name: ups
dtype: int64
- name: downs
dtype: int64
- name: date
dtype: string
- name: created_utc
dtype: int64
- name: subreddit
dtype: string
- name: id
dtype: string
splits:
- name: train
num_bytes: 1764500045
num_examples: 12704751
download_size: 903559115
dataset_size: 1764500045
license: cc-by-2.0
SARC_Sarcasm
Dataset Description
Dataset Summary
A large corpus for sarcasm research and for training and evaluating systems for sarcasm detection is presented. The corpus comprises 1.3 million sarcastic statements, a quantity that is tenfold more substantial than any preceding dataset, and includes many more instances of non-sarcastic statements. This allows for learning in both balanced and unbalanced label regimes. Each statement is self-annotated; that is to say, sarcasm is labeled by the author, not by an independent annotator, and is accompanied by user, topic, and conversation context. The accuracy of the corpus is evaluated, benchmarks for sarcasm detection are established, and baseline methods are assessed.
For the details of this dataset, we refer you to the original paper.
Metadata in Creative Language Toolkit (CLTK)
- CL Type: Sarcasm
- Task Type: detection
- Size: 1.3M
- Created time: 2018
Contributions
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