Comparing all-author and first-author co-citation analyses of information science

摘要: Abstract Although it is generally understood that different citation counting methods can produce quite author rankings, and although “optimal” co-citation have been identified theoretically, studies compare in analysis (ACA) are still rare. The present study applies strict all-author-based ACA to the Information Science (IS) field, all authors of cited references a classic IS dataset counted, even diagonal values matrix computed their theoretically optimal form. Using Scopus instead SSCI as data source, we find results from all-author appear be excellent practice, too, field like where co-authorship levels relatively low, its advantages over first-author considerably smaller than more highly collaborative ones targeted before. Nevertheless, do some differences between two approaches, appears favor theorists who presumably tend work alone, while paint somewhat recent picture pick out clusters.