Purpose This study was conducted to understand the perceptions and awareness of artificial intelligence (AI) in the academic publishing landscape.
Methods We conducted a global survey entitled “Role and impact of AI on the future of academic publishing” to understand the impact of the AI wave in the scholarly publishing domain. This English-language survey was open to all researchers, authors, editors, publishers, and other stakeholders in the scholarly community. Conducted between August and October 2021, the survey received responses from around 212 universities across 54 countries.
Results Out of 365 respondents, about 93% belonged to the age groups of 18–34 and 35–54 years. While 50% of the respondents selected plagiarism detection as the most widely known AI-based application, image recognition (42%), data analytics (40%), and language enhancement (39%) were some other known applications of AI. The respondents also expressed the opinion that the academic publishing landscape will significantly benefit from AI. However, the major challenges restraining the large-scale adoption of AI, as expressed by 93% of the respondents, were limited knowledge and expertise, as well as difficulties in integrating AI-based solutions into existing IT infrastructure.
Conclusion The survey responses reflected the necessity of AI in research and publishing. This study suggests possible ways to support a smooth transition. This can be best achieved by educating and creating awareness to ease possible fears and hesitation, and to actualize the promising benefits of AI.
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Purpose Although North Korea invests in scientific research, few selected research results are published to international journals. However, the latest peaceful political developments around North Korea have increased concerns about how they will support international scientific cooperation. This study aims to analyze the scientific collaboration and intellectual structure of North Korean researchers.
Methods We conducted a co-word analysis with author keywords and author names using the Web of Science records for 1976–2018 to observe the changes in research trends in North Korea. The structure of the median centrality of words and the parallel nearest neighbor clustering methods were used to visualize the results.
Results The analysis of 55 final keywords confirms that the corresponding network is composed of 17 sub-clusters under four areas. As a result of the investigation of 56 final author names, the corresponding network is composed of 15 sub-clusters under four areas.
Conclusion As more accurate information is needed about collaboration partners to ensure successful cooperation, this analysis result can support getting an overview of North Korea’s research community and their research network.
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