A Platform to Explore ChatGPT's Performance on News Recommendation Related Tasks
Welcome to ChatNews, a dedicated platform designed for researchers and users of ChatGPT to explore news recommendation and the potential of ChatGPT in this field. With its user-friendly interface and growing user base, ChatGPT has become a popular choice for text-based tasks. Recognizing the importance of news recommendation in addressing societal issues and the increasing use of language models for recommendations, we have created ChatNews. Our platform provides an inclusive environment for researchers to investigate how different prompt formats can significantly impact ChatGPT's performance. We aim to determine whether specific prompt formats can enhance ChatGPT's capabilities in news recommendation and identify areas for further research. At ChatNews, we go beyond static assessments by actively monitoring and analyzing ChatGPT's real-time performance on various tasks. We encourage all ChatGPT users to contribute and share their findings, contributing to our collective understanding of ChatGPT's abilities in news recommendation.
The small test samples can be downloaded below or be found on Github https://anonymous.4open.science/r/ChatGPT-News-3E94.
We examine the effectiveness of ChatGPT from three different perspectives: personalization, news provider fairness, and fake news. The responses generated by ChatGPT are randomized, to track the dynamic performance of each prompt for each task, we only utilize each prompt once per user.
Now it's your opportunity to share your discoveries. Have you identified any additional problems with ChatGPT's responses for news recommendations? Have you found any methods to address these problems by improving the prompt format of ChatGPT? Please share your findings with us. A more comprehensive dataset on Microsoft News Dataset can be found https://msnews.github.io for your study.