Summary of Exploring the Capability Of Chatgpt to Reproduce Human Labels For Social Computing Tasks (extended Version), by Yiming Zhu et al.
Exploring the Capability of ChatGPT to Reproduce Human Labels for Social Computing Tasks (Extended Version)
by Yiming Zhu, Peixian Zhang, Ehsan-Ul Haq, Pan Hui, Gareth Tyson
First submitted to arxiv on: 8 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary ChatGPT shows promise in handling data annotation tasks related to pressing social issues, such as COVID-19 misinformation, social bot deception, cyberbully, clickbait news, and the Russo-Ukrainian War. Researchers re-annotate seven datasets using ChatGPT, achieving an average F1-score of 72.00% across the datasets, with excellent performance in clickbait news annotation (89.66%). However, significant variations are observed in performance across individual labels. The study proposes GPT-Rater, a tool to predict if ChatGPT can correctly label data for a given annotation task, which effectively predicts ChatGPT’s performance, especially on clickbait headlines datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ChatGPT is helping people with big social problems like misinformation and cyberbullying by labeling data accurately. The paper looks at how well ChatGPT does this task and finds that it can do it pretty well, but not always perfectly. It even makes a special tool to predict when ChatGPT will get something right or wrong, which is really helpful for researchers. |
Keywords
* Artificial intelligence * F1 score * Gpt
