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Wang, Y.; Lee, J.-S.; Choi, I.-C.: Indexing by Latent Dirichlet Allocation and an Ensemble Model (2016)
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- Date
- 12. 6.2016 21:39:22
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Wang, Y.; Shah, C.: Investigating failures in information seeking episodes (2017)
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- Date
- 20. 1.2015 18:30:22
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Zhang, C.; Liu, X.; Xu, Y.(C.); Wang, Y.: Quality-structure index : a new metric to measure scientific journal influence (2011)
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Xie, B.; He, D.; Mercer, T.; Wang, Y.; Wu, D.; Fleischmann, K.R.; Zhang, Y.; Yoder, L.H.; Stephens, K.K.; Mackert, M.; Lee, M.K.: Global health crises are also information crises : a call to action (2020)
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- Abstract
- In this opinion paper, we argue that global health crises are also information crises. Using as an example the coronavirus disease 2019 (COVID-19) epidemic, we (a) examine challenges associated with what we term "global information crises"; (b) recommend changes needed for the field of information science to play a leading role in such crises; and (c) propose actionable items for short- and long-term research, education, and practice in information science.
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Wu, S.; Liu, S.; Wang, Y.; Timmons, T.; Uppili, H.; Bedrick, S.; Hersh, W.; Liu, H,: Intrainstitutional EHR collections for patient-level information retrieval (2017)
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Huang, C.; Zha, X.; Yan, Y.; Wang, Y.: Understanding the social structure of academic social networking sites : the case of ResearchGate (2019)
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Wang, Y.; Shah, C.: Authentic versus synthetic : an investigation of the influences of study settings and task configurations on search behaviors (2022)
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Cui, Y.; Wang, Y.; Liu, X.; Wang, X.; Zhang, X.: Multidimensional scholarly citations : characterizing and understanding scholars' citation behaviors (2023)
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- Abstract
- This study investigates scholars' citation behaviors from a fine-grained perspective. Specifically, each scholarly citation is considered multidimensional rather than logically unidimensional (i.e., present or absent). Thirty million articles from PubMed were accessed for use in empirical research, in which a total of 15 interpretable features of scholarly citations were constructed and grouped into three main categories. Each category corresponds to one aspect of the reasons and motivations behind scholars' citation decision-making during academic writing. Using about 500,000 pairs of actual and randomly generated scholarly citations, a series of Random Forest-based classification experiments were conducted to quantitatively evaluate the correlation between each constructed citation feature and citation decisions made by scholars. Our experimental results indicate that citation proximity is the category most relevant to scholars' citation decision-making, followed by citation authority and citation inertia. However, big-name scholars whose h-indexes rank among the top 1% exhibit a unique pattern of citation behaviors-their citation decision-making correlates most closely with citation inertia, with the correlation nearly three times as strong as that of their ordinary counterparts. Hopefully, the empirical findings presented in this paper can bring us closer to characterizing and understanding the complex process of generating scholarly citations in academia.
