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<record>
  <title>Exploring Authorship Patterns in Artif icial Intelligence Literature in Library Science: A Bibliometric Analysis</title>
  <journal>Journal of Science and Technology Metrics</journal>
  <author>Bhuvaneshwari Patil, Gavisiddappa Anandhalli</author>
  <volume>5</volume>
  <issue>3</issue>
  <year>2024</year>
  <doi>https://doi.org/10.6025/jstm/2024/5/3/89-98</doi>
  <url>https://www.dline.info/jstm/fulltext/v5n3/jstmv5n3_4.pdf</url>
  <abstract>This study examines the authorship pattern and research collaboration in Artificial
Intelligence (AI) based on 3495 scholarly communications between 2014 and 2023.
The analysis delves into various significant aspects such as types and trends of
authorship, author productivity, author per paper, Document-wise distribution, and
geographical distribution. Notably, multiple-author papers emerge as more prevalent
within AI. Additionally, the study identifies the USA as the highest contributor
country in AI.</abstract>
</record>
