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Purpose: Academic and other researchers have limited tools with which to address the current proliferation of predatory and hijacked journals. These journals can have negative effects on science, research funding, and the dissemination of information. As most predatory and hijacked journals are not error free, this study used ChatGPT, an artificial intelligence (AI) technology tool, to conduct an evaluation of journal quality. Methods: Predatory and hijacked journals were analyzed for reliability using ChatGPT, and the reliability of result have been discussed. Results: It shows that ChatGPT is an unreliable tool for journal quality evaluation for both hijacked and predatory journals. Conclusion: To show how to address this gap, an early trial version of Journal Checker Chatbot has been developed and is discussed as an alternative chatbot that can assist researchers in detecting hijacked journals. [ABSTRACT FROM AUTHOR]

Predatory journals are a well-known issue for scholarly publishing and they are repositories for bogus research. In recent years, the number of predatory journals has risen and it is necessary to present a solution for this challenge. In this paper, we will discuss about a possible ranking of predatory journals. Our ranking approach is based on Beall's criteria for detection of predatory journals and it can help editors to improve their journals or convert their questionable journals to non-predatory ones. Moreover, our approach could help young editors to protect their journals against predatory practice. Finally, we present a case study to clarify our approach. [ABSTRACT FROM AUTHOR]