Dataset Card for ConcluGen
Table of Contents
- Dataset Card for ConcluGen
Dataset Description
- Homepage: https://zenodo.org/record/4818134
- Repository: https://github.com/webis-de/acl21-informative-conclusion-generation
- Paper: Generating Informative Conclusions for Argumentative Texts
- Leaderboard: [N/A]
- Point of Contact: [email protected]
Dataset Summary
The ConcluGen corpus is constructed for the task of argument summarization. It consists of 136,996 pairs of argumentative texts and their conclusions collected from the ChangeMyView subreddit, a web portal for argumentative discussions on controversial topics.
The corpus has three variants: aspects, topics, and targets. Each variation encodes the corresponding information via control codes. These provide additional argumentative knowledge for generating more informative conclusions.
Supported Tasks and Leaderboards
Argument Summarization, Conclusion Generation
Languages
English ('en') as spoken by Reddit users on the r/changemyview subreddits.
Dataset Structure
Data Instances
An example consists of a unique 'id', an 'argument', and its 'conclusion'.
{'id': 'ee11c116-23df-4795-856e-8b6c6626d5ed',
'argument': "In my opinion, the world would be a better place if alcohol was illegal. I've done a little bit of research to get some numbers, and I was quite shocked at what I found. Source On average, one in three people will be involved in a drunk driving crash in their lifetime. In 2011, 9,878 people died in drunk driving crashes Drunk driving costs each adult in this country almost 500 per year. Drunk driving costs the United States 132 billion a year. Every day in America, another 27 people die as a result of drunk driving crashes. Almost every 90 seconds, a person is injured in a drunk driving crash. These are just the driving related statistics. They would each get reduced by at least 75 if the sale of alcohol was illegal. I just don't see enough positives to outweigh all the deaths and injuries that result from irresponsible drinking. Alcohol is quite literally a drug, and is also extremely addicting. It would already be illegal if not for all these pointless ties with culture. Most people wouldn't even think to live in a world without alcohol, but in my opinion that world would be a better, safer, and more productive one. , or at least defend the fact that it's legal.",
'conclusion': 'I think alcohol should be illegal.'}
Data Fields
id: a string identifier for each example.argument: the argumentative text.conclusion: the conclusion of the argumentative text.
Data Splits
The data is split into train, validation, and test splits for each variation of the dataset (including base).
| | Train | Validation | Test | |--------- |--------- |------------ |------ | | Base | 123,539 | 12,354 | 1373 | | Aspects | 122,040 | 12,192 | 1359 | | Targets | 110,867 | 11,068 | 1238 | | Topic | 123,538 | 12,354 | 1374 |
Dataset Creation
Curation Rationale
ConcluGen was built as a first step towards argument summarization technology. The rules of the subreddit ensure high quality data suitable for the task.
Source Data
Initial Data Collection and Normalization
Reddit ChangeMyView
Who are the source language producers?
Users of the subreddit r/chanhemyview. Further demographic information is unavailable from the data source.
Annotations
The dataset is augmented with automatically extracted knowledge such as the argument's aspects, the discussion topic, and possible conclusion targets.
Annotation process
[N/A]
Who are the annotators?
[N/A]
Personal and Sensitive Information
Only the argumentative text and its conclusion are provided. No personal information of the posters is included.
Considerations for Using the Data
Social Impact of Dataset
[Needs More Information]
Discussion of Biases
[Needs More Information]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
[Needs More Information]
Licensing Information
The licensing status of the dataset hinges on the legal status of the Pushshift.io data which is unclear.
Citation Information
@inproceedings{syed:2021,
author = {Shahbaz Syed and
Khalid Al Khatib and
Milad Alshomary and
Henning Wachsmuth and
Martin Potthast},
editor = {Chengqing Zong and
Fei Xia and
Wenjie Li and
Roberto Navigli},
title = {Generating Informative Conclusions for Argumentative Texts},
booktitle = {Findings of the Association for Computational Linguistics: {ACL/IJCNLP}
2021, Online Event, August 1-6, 2021},
pages = {3482--3493},
publisher = {Association for Computational Linguistics},
year = {2021},
url = {https://doi.org/10.18653/v1/2021.findings-acl.306},
doi = {10.18653/v1/2021.findings-acl.306}
}