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Kim, J.: Describing and predicting information-seeking behavior on the Web (2009)
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- Date
- 22. 3.2009 18:54:15
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Kang, I.-S.; Na, S.-H.; Kim, J.; Lee, J.-H.: Cluster-based patent retrieval (2007)
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Kim, J.; Diesner, J.: Coauthorship networks : a directed network approach considering the order and number of coauthors (2015)
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- Abstract
- In many scientific fields, the order of coauthors on a paper conveys information about each individual's contribution to a piece of joint work. We argue that in prior network analyses of coauthorship networks, the information on ordering has been insufficiently considered because ties between authors are typically symmetrized. This is basically the same as assuming that each coauthor has contributed equally to a paper. We introduce a solution to this problem by adopting a coauthorship credit allocation model proposed by Kim and Diesner (2014), which in its core conceptualizes coauthoring as a directed, weighted, and self-looped network. We test and validate our application of the adopted framework based on a sample data of 861 authors who have published in the journal Psychometrika. The results suggest that this novel sociometric approach can complement traditional measures based on undirected networks and expand insights into coauthoring patterns such as the hierarchy of collaboration among scholars. As another form of validation, we also show how our approach accurately detects prominent scholars in the Psychometric Society affiliated with the journal.
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Kim, J.; Diesner, J.: Distortive effects of initial-based name disambiguation on measurements of large-scale coauthorship networks (2016)
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- Abstract
- Scholars have often relied on name initials to resolve name ambiguities in large-scale coauthorship network research. This approach bears the risk of incorrectly merging or splitting author identities. The use of initial-based disambiguation has been justified by the assumption that such errors would not affect research findings too much. This paper tests that assumption by analyzing coauthorship networks from five academic fields-biology, computer science, nanoscience, neuroscience, and physics-and an interdisciplinary journal, PNAS. Name instances in data sets of this study were disambiguated based on heuristics gained from previous algorithmic disambiguation solutions. We use disambiguated data as a proxy of ground-truth to test the performance of three types of initial-based disambiguation. Our results show that initial-based disambiguation can misrepresent statistical properties of coauthorship networks: It deflates the number of unique authors, number of components, average shortest paths, clustering coefficient, and assortativity, while it inflates average productivity, density, average coauthor number per author, and largest component size. Also, on average, more than half of top 10 productive or collaborative authors drop off the lists. Asian names were found to account for the majority of misidentification by initial-based disambiguation due to their common surname and given name initials.
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Walsh, J.A.; Cobb, P.J.; Fremery, W. de; Golub, K.; Keah, H.; Kim, J.; Kiplang'at, J.; Liu, Y.-H.; Mahony, S.; Oh, S.G.; Sula, C.A.; Underwood, T.; Wang, X.: Digital humanities in the iSchool (2022)
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Yakel, E.; Kim, J.: Adoption and diffusion of Encoded Archival Description (2005)
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- Abstract
- In this article, findings from a study an the diffusion and adoption of Encoded Archival Description (EAD) within the U.S. archival community are reported. Using E. M. Rogers' (1995) theory of the diffusion of innovations as a theoretical framework, the authors surveyed 399 archives and manuscript repositories that sent participants to EAD workshops from 1993-2002. Their findings indicated that EAD diffusion and adoption are complex phenomena. While the diffusion pattern mirrored that of MAchine-Readable Cataloging (MARC), overall adoption was slow. Only 42% of the survey respondents utilized EAD in their descriptive programs. Critical factors inhibiting adoption include the small staff size of many repositories, the lack of standardization in archival descriptive practices, a multiplicity of existing archival access tools, insufficient institutional infrastructure, and difficulty in maintaining expertise.
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Kim, J.: Author-based analysis of conference versus journal publication in computer science (2019)
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- Abstract
- Conference publications in computer science (CS) have attracted scholarly attention due to their unique status as a main research outlet, unlike other science fields where journals are dominantly used for communicating research findings. One frequent research question has been how different conference and journal publications are, considering an article as a unit of analysis. This study takes an author-based approach to analyze the publishing patterns of 517,763 scholars who have ever published both in CS conferences and journals for the last 57 years, as recorded in DBLP. The analysis shows that the majority of CS scholars tend to make their scholarly debut, publish more articles, and collaborate with more coauthors in conferences than in journals. Importantly, conference articles seem to serve as a distinct channel of scholarly communication, not a mere preceding step to journal publications: coauthors and title words of authors across conferences and journals tend not to overlap much. This study corroborates findings of previous studies on this topic from a distinctive perspective and suggests that conference authorship in CS calls for more special attention from scholars and administrators outside CS who have focused on journal publications to mine authorship data and evaluate scholarly performance.
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Kim, J.; Thomas, P.; Sankaranarayana, R.; Gedeon, T.; Yoon, H.-J.: Eye-tracking analysis of user behavior and performance in web search on large and small screens (2015)
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Kim, J.; Thomas, P.; Sankaranarayana, R.; Gedeon, T.; Yoon, H.-J.: Understanding eye movements on mobile devices for better presentation of search results (2016)
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