CreativeLang/EPIC_Irony

---
dataset_info:
features:
- name: user
dtype: string
- name: label
dtype: string
- name: timestamp
dtype: string
- name: source
dtype: string
- name: subreddit
dtype: string
- name: id_original
dtype: string
- name: text
dtype: string
- name: parent_id_original
dtype: string
- name: parent_text
dtype: string
- name: Language_instance
dtype: string
- name: Language_variety
dtype: string
- name: Age
dtype: string
- name: Sex
dtype: string
- name: Ethnicity simplified
dtype: string
- name: Country of birth
dtype: string
- name: Country of residence
dtype: string
- name: Nationality
dtype: string
- name: Language_annotator
dtype: string
- name: Student status
dtype: string
- name: Employment status
dtype: string
splits:
- name: train
num_bytes: 7299373
num_examples: 14172
download_size: 1038853
dataset_size: 7299373
---
# EPIC_Irony

- paper: [EPIC: Multi-Perspective Annotation of a Corpus of Irony](https://assets.amazon.science/40/b4/0f6ec06a4a33a44485de1b2b57c7/epic-multi-perspective-annotation-of-a-corpus-of-irony.pdf) at ACL 2023

Key features:

- EPIC (English Perspectivist Irony Corpus) is an annotated corpus for irony analysis based on data perspectivism principles.
- The corpus contains social media conversations in five regional varieties of English, annotated by contributors from corresponding countries.
- The dataset explores the perspectives of annotators, taking into account their origin, age, and gender.
- Perspective-aware models were created to validate EPIC, and these proved more effective and confident in identifying irony than non-perspectivist models.
- The models showcase variation in irony perception across different demographic groups.
- EPIC serves as a valuable resource for training perspective-aware models for irony detection.

Metadata in Creative Language Toolkit ([CLTK](https://github.com/liyucheng09/cltk))
- CL Type: Irony
- Task Type: detection
- Size: 14k
- Created time: 2023

原始信息汇总

数据集概述

数据集名称

• 名称: EPIC_Irony

数据集特征

• 特征列表:
  • user
  • label
  • timestamp
  • source
  • subreddit
  • id_original
  • text
  • parent_id_original
  • parent_text
  • Language_instance
  • Language_variety
  • Age
  • Sex
  • Ethnicity simplified
  • Country of birth
  • Country of residence
  • Nationality
  • Language_annotator
  • Student status
  • Employment status
• 数据类型: 所有特征均为字符串类型 (dtype: string)

数据集分割

• 分割:
  • 名称: train
  • 大小:
    • 字节数: 7299373
    • 示例数: 14172

数据集大小

• 下载大小: 1038853 字节
• 数据集大小: 7299373 字节

数据集用途

• 用途: 用于训练和验证视角感知模型，特别是用于讽刺检测。
• 特点:
  • 基于数据视角主义原则的讽刺分析注释语料库。
  • 包含五种地区英语变体的社交媒体对话，由相应国家的贡献者注释。
  • 探索注释者的视角，考虑其原籍、年龄和性别。
  • 展示不同人口统计群体在讽刺感知上的变化。
  • 作为训练视角感知模型进行讽刺检测的宝贵资源。