Datasets:
metadata
annotations_creators:
- crowdsourced
- expert-generated
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
paperswithcode_id: humicroedit
pretty_name: Humicroedit
configs:
- subtask-1
- subtask-2
tags:
- funnier-headline-identification
- funniness-score-prediction
dataset_info:
- config_name: subtask-1
features:
- name: id
dtype: string
- name: original
dtype: string
- name: edit
dtype: string
- name: grades
dtype: string
- name: meanGrade
dtype: float32
splits:
- name: train
num_bytes: 1058589
num_examples: 9652
- name: test
num_bytes: 332113
num_examples: 3024
- name: validation
num_bytes: 269083
num_examples: 2419
- name: funlines
num_bytes: 942376
num_examples: 8248
download_size: 1621456
dataset_size: 2602161
- config_name: subtask-2
features:
- name: id
dtype: string
- name: original1
dtype: string
- name: edit1
dtype: string
- name: grades1
dtype: string
- name: meanGrade1
dtype: float32
- name: original2
dtype: string
- name: edit2
dtype: string
- name: grades2
dtype: string
- name: meanGrade2
dtype: float32
- name: label
dtype:
class_label:
names:
'0': equal
'1': sentence1
'2': sentence2
splits:
- name: train
num_bytes: 2102667
num_examples: 9381
- name: test
num_bytes: 665087
num_examples: 2960
- name: validation
num_bytes: 535044
num_examples: 2355
- name: funlines
num_bytes: 451416
num_examples: 1958
download_size: 1621456
dataset_size: 3754214
Dataset Card for [Dataset Name]
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:Humicroedit
- Repository:
- Paper:"President Vows to Cut Taxes Hair": Dataset and Analysis of Creative Text Editing for Humorous Headlines.
- Leaderboard:
- Point of Contact:[nhossain@cs.rochester.edu]
Dataset Summary
This is the task dataset for SemEval-2020 Task 7: Assessing Humor in Edited News Headlines.
Supported Tasks and Leaderboards
- Regression Task: In this task, given the original and the edited headline, the participant is required to predict the mean funniness of the edited headline. Success on this task is typically measured by achieving a low Mean Square Error.
- Predict the funnier of the two edited headlines: Given the original headline and two edited versions, the participant has to predict which edited version is the funnier of the two. Success on this task is typically measured by achieving a high accuracy.
Languages
English
Dataset Structure
Data Instances
For subtask-1, i.e Given the original and the edited headline, predict the mean funniness of the edited headline.
{
'id': 1183,
'original': 'Kushner to visit <Mexico/> following latest trump tirades.',
'edit': 'therapist',
'grades': '33332',
'meanGrade': 2.8
}
For subtask-2, i.e Given the original headline and two edited versions, predict which edited version is the funnier of the two.
{
'id': 1183,
'original1': 'Gene Cernan , Last <Astronaut/> on the Moon , Dies at 82',
'edit1': 'Dancer',
'grades1': '1113',
'meanGrade1': 1.2,
'original2': 'Gene Cernan , Last Astronaut on the Moon , <Dies/> at 82',
'edit2': 'impregnated',
'grades2': '30001',
'meanGrade2': 0.8,
'label': 1
}
Data Fields
For subtask-1
id: Unique identifier of an edited headline.original: The headline with replaced word(s) identified with the </> tag.edit: The new word which replaces the word marked in </> tag in the original field.grades: 'grades' are the concatenation of all the grades by different annotators.meanis the mean of all the judges scores.
For subtask-2
id: Unique identifier of an edited headline.original1: The original headline with replaced word(s) identified with </> tag.edit1: The new word which replaces the word marked in </> tag in theoriginal1field.grades1: The concatenation of all the grades annotated by different annotators for sentence1.meanGrade1is the mean of all the judges scores for sentence1.original2: The original headline with replaced word(s) identified with </> tag.edit2: The new word which replaces the word marked in </> tag in theoriginal1field.grades2: The concatenation of all the grades annotated by different annotators for the sentence2.meanGrade2is the mean of all the judges scores for sentence2.labelis 1 if sentence1 is more humourous than sentence2, 2 if sentence 2 is more humorous than sentence1, 0 if both the sentences are equally humorous
Data Splits
| Sub Task | Train | Dev | Test | Funlines |
|---|---|---|---|---|
| Subtask-1:Regression | 9652 | 2419 | 3024 | 8248 |
| Subtask-2: Funnier headline prediction | 9381 | 2355 | 2960 | 1958 |
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
Crowd-sourced the data by gamifying it as on the website funlines.co. Players rate the headlines on a scale of 0-4. Players are scored based on their editing and rating, and they are ranked on the game’s leaderboard page.
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@article{hossain2019president,
title={" President Vows to Cut< Taxes> Hair": Dataset and Analysis of Creative Text Editing for Humorous Headlines},
author={Hossain, Nabil and Krumm, John and Gamon, Michael},
journal={arXiv preprint arXiv:1906.00274},
year={2019}
}```
### Contributions
Thanks to [@saradhix](https://github.com/saradhix) for adding this dataset.