-
Zhang, Y.: Developing a holistic model for digital library evaluation (2010)
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- Abstract
- This article reports the author's recent research in developing a holistic model for various levels of digital library (DL) evaluation in which perceived important criteria from heterogeneous stakeholder groups are organized and presented. To develop such a model, the author applied a three-stage research approach: exploration, confirmation, and verification. During the exploration stage, a literature review was conducted followed by an interview, along with a card sorting technique, to collect important criteria perceived by DL experts. Then the criteria identified were used for developing an online survey during the confirmation stage. Survey respondents (431 in total) from 22 countries rated the importance of the criteria. A holistic DL evaluation model was constructed using statistical techniques. Eventually, the verification stage was devised to test the reliability of the model in the context of searching and evaluating an operational DL. The proposed model fills two lacunae in the DL domain: (a) the lack of a comprehensive and flexible framework to guide and benchmark evaluations, and (b) the uncertainty about what divergence exists among heterogeneous DL stakeholders, including general users.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.1, S.88-110
-
Zhang, Y.: Scholarly use of Internet-based electronic resources (2001)
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- Date
- 17. 7.2006 13:06:26
- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.8, S.628-654
-
Zhang, M.; Zhang, Y.: Professional organizations in Twittersphere : an empirical study of U.S. library and information science professional organizations-related Tweets (2020)
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- Abstract
- Twitter is utilized by many, including professional businesses and organizations; however, there are very few studies on how other entities interact with these organizations in the Twittersphere. This article presents a study that investigates tweets related to 5 major library and information science (LIS) professional organizations in the United States. This study applies a systematic tweets analysis framework, including descriptive analytics, network analytics, and co-word analysis of hashtags. The findings shed light on user engagement with LIS professional organizations and the trending discussion topics on Twitter, which is valuable for enabling more successful social media use and greater influence.
-
Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009)
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- Date
- 22. 3.2009 17:49:11
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
-
Lu, C.; Zhang, Y.; Ahn, Y.-Y.; Ding, Y.; Zhang, C.; Ma, D.: Co-contributorship network and division of labor in individual scientific collaborations (2020)
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- Abstract
- Collaborations are pervasive in current science. Collaborations have been studied and encouraged in many disciplines. However, little is known about how a team really functions from the detailed division of labor within. In this research, we investigate the patterns of scientific collaboration and division of labor within individual scholarly articles by analyzing their co-contributorship networks. Co-contributorship networks are constructed by performing the one-mode projection of the author-task bipartite networks obtained from 138,787 articles published in PLoS journals. Given an article, we define 3 types of contributors: Specialists, Team-players, and Versatiles. Specialists are those who contribute to all their tasks alone; team-players are those who contribute to every task with other collaborators; and versatiles are those who do both. We find that team-players are the majority and they tend to contribute to the 5 most common tasks as expected, such as "data analysis" and "performing experiments." The specialists and versatiles are more prevalent than expected by our designed 2 null models. Versatiles tend to be senior authors associated with funding and supervision. Specialists are associated with 2 contrasting roles: the supervising role as team leaders or marginal and specialized contributors.
-
Zhang, Y.: Using the Internet for survey research : a case study (2000)
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- Source
- Journal of the American Society for Information Science. 51(2000) no.1, S.57-68
-
Zhang, Y.: Searching for specific health-related information in MedlinePlus : behavioral patterns and user experience (2014)
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- Date
- 26. 1.2014 19:07:54
-
Chung, W.; Zhang, Y.; Huang, Z.; Wang, G.; Ong, T.-H.; Chen, H.: Internet searching and browsing in a multilingual world : an experiment an the Chinese Business Intelligence Portal (CBizPort) (2004)
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- Source
- Journal of the American Society for Information Science and Technology. 55(2004) no.9, S.818-831
-
Zhang, Y.; Li, Y.: ¬A user-centered functional metadata evaluation of moving image collections (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.8, S.1331-1346
-
Zhang, Y.: Undergraduate students' mental models of the Web as an information retrieval system (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2087-2098
-
Dang, Y.; Zhang, Y.; Chen, H.; Hu, P.J.-H.; Brown, S.A.; Larson, C.: Arizona Literature Mapper : an integrated approach to monitor and analyze global bioterrorism research literature (2009)
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- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.7, S.1466-1485
-
Zhang, Y.: Dimensions and elements of people's mental models of an information-rich Web space (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.11, S.2206-2218
-
Zhang, Y.: Toward a layered model of context for health information searching : an analysis of consumer-generated questions (2013)
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- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.6, S.1158-1172
-
Zhang, Y.; Kudva, S.: E-books versus print books : readers' choices and preferences across contexts (2014)
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- Abstract
- With electronic book (e-book) sales and readership rising, are e-books positioned to replace print books? This study examines the preference for e-books and print books in the contexts of reading purpose, reading situation, and contextual variables such as age, gender, education level, race/ethnicity, income, community type, and Internet use. In addition, this study aims to identify factors that contribute to e-book adoption. Participants were a nationally representative sample of 2,986 people in the United States from the Reading Habits Survey, conducted by the Pew Research Center's Internet & American Life Project (http://pewinternet.org/Shared-Content/Data-Sets/2011/December-2011--Reading-Habits.aspx). While the results of this study support the notion that e-books have firmly established a place in people's lives, due to their convenience of access, e-books are not yet positioned to replace print books. Both print books and e-books have unique attributes and serve irreplaceable functions to meet people's reading needs, which may vary by individual demographic, contextual, and situational factors. At this point, the leading significant predictors of e-book adoption are the number of books read, the individual's income, the occurrence and frequency of reading for research topics of interest, and the individual's Internet use, followed by other variables such as race/ethnicity, reading for work/school, age, and education.
-
Zhang, Y.: ¬The impact of Internet-based electronic resources on formal scholarly communication in the area of library and information science : a citation analysis (1998)
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- Date
- 30. 1.1999 17:22:22
-
Zhang, Y.; Liu, J.; Song, S.: ¬The design and evaluation of a nudge-based interface to facilitate consumers' evaluation of online health information credibility (2023)
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- Date
- 22. 6.2023 18:18:34
-
Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023)
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- Date
- 22. 6.2023 18:07:12
