| --- |
| license: cc-by-4.0 |
| task_categories: |
| - text-classification |
| language: |
| - zh |
| tags: |
| - fact-checking |
| - misinformation |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # TrendFact |
|
|
| TrendFact is the Chinese fact-checking benchmark from our ACL 2026 paper *TrendFact: A Benchmark Towards Hotspot Perception in Automatic Fact-Checking*. |
|
|
| Unlike earlier datasets built mostly on Wikipedia, most claims in TrendFact are drawn from trending platforms, so every sample comes with real dissemination signals. We use it to study a mostly overlooked question: when claims differ in social impact, should — and can — a fact-checking system adapt how much reasoning effort it spends on them? We call this the Hotspot Perception Ability (HPA). |
|
|
| ## Data |
|
|
| - **7,643** samples across five domains: public health, science, society, politics, and culture |
| - an evidence library of **366,634** entries |
| - supports three tasks: evidence retrieval, fact verification, and explanation generation |
|
|
| ### `TrendFact.json` |
|
|
| The main data. Each sample has the following fields: |
|
|
| | Field | Description | |
| |-------|-------------| |
| | `claim` | the claim to be verified | |
| | `label` | 0 = SUPPORT, 1 = REFUTE, 2 = NEI (not enough info) | |
| | `evidence` | gold evidence, with `text` / `url` / `target_idx` | |
| | `explanation` | human-annotated explanation | |
| | `domain` | domain the claim belongs to | |
| | `views` / `Discussion` / `Engagemen` / `Post` | four hotspot indicators | |
| | `influence_score` / `final_influence_score` | influence scores | |
| | `ori_title` / `url` / `date` | original title, source link, and date of the claim | |
|
|
| ### `evidence.parquet` |
|
|
| The evidence library, 366,634 entries in total, with fields `url` / `text` / `publish_date`. Used for the evidence retrieval task. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{zhang2026trendfact, |
| title={TrendFact: A Benchmark Towards Hotspot Perception in Automatic Fact-Checking}, |
| author={Zhang, Xiaocheng and Wang, Xi and Lu, Yifei and Wang, Jianing and Ye, Zhuangzhuang and Bao, Mengjiao and Yan, Peng and Su, Xiaohong}, |
| booktitle={Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)}, |
| pages={26494--26513}, |
| year={2026} |
| } |
| ``` |
|
|
| Code: https://github.com/zxc123cc/TrendFact |
|
|
