ClaimDiff

This repository contains the data for our paper: Miyoung Ko, Ingyu Seong, Hwaran Lee, Joonsuk Park, Minsuk Chang, Minjoon Seo. "ClaimDiff: Comparing and Contrasting Claims on Contentious Issues".

• Please contact Miyoung Ko [email protected] and Ingyu Seong [email protected], or leave Github issues for suggestions and comments.
• For more details about this dataset, see the paper.

Dataset

Data

The ClaimDiff dataset includes 2,941 claim pairs extracted from 274 articles with 137 topics. We extract the pairs from a group of articles sharing the same topic, released by multiple presses. The diverse views on contentious topics can be obtained by collecting the claims written by different authors and presses. We present the ClaimDiff dataset as ClaimDiff-S and ClaimDiff-W, which is as follows:

🗃 ClaimDiff

├── 📁 ClaimDiff-S
│   ├── ClaimDiff-strength-train.json
│   ├── ClaimDiff-strength-test.json
│   └── ClaimDiff-strength-test-full.json
├── 📁 ClaimDiff-W
│   ├── ClaimDiff-weak-train.json
│   ├── ClaimDiff-weak-test.json
│   └── ClaimDiff-weak-test-full.json
└── annotation_result_unfiltered.json

Statistics

We release our main ClaimDiff dataset {Train, Test} along with an additional Test-full dataset. Test-full can be considered an unfiltered test dataset to encounter the real-world distribution over whole articles, resulting in a high ratio of unrelated pairs.

	Train	Test	Test-full
Pairs	1,857	1,084	3,173
Topics	90	44	44
Articles	180	88	88
% Strengthen	69.31%	56.64%	19.35%
% Weaken	10.61%	21.96%	7.50%

Data Format

ClaimDiff-{strength,weak}-{train,test,test-full}.json files contains a list of dictionary that represents a single instance, with the following keys:

{
	"topic": "str(Topic of the claim pair)",
	"date": "str(Published date of Article A)",
	"pair_id": "str(Unique pair ID)",
	"claim_a": "str(Claim A from Article A, c_1)",
	"claim_b": "str(Claim B from Article B, c_2)",
	"article_a": "str(Title of Article A)",
	"article_b": "str(Title of Article B)",
	"relation": "int(0 or 1)",
	"rationale": "List[str]",
}

annotation_result_unfiltered.json files contain a list of items with average response score before filtering. This list also includes examples with average scores between (-0.5, 0.5).

Citation

Please cite our paper in your publications if you find the ClaimDiff dataset useful:

@misc{ko2023claimdiff,
      title={ClaimDiff: Comparing and Contrasting Claims on Contentious Issues}, 
      author={Miyoung Ko and Ingyu Seong and Hwaran Lee and Joonsuk Park and Minsuk Chang and Minjoon Seo},
      year={2023},
      eprint={2205.12221},
      archivePrefix={arXiv},
}