Search (28 results, page 1 of 2)

  • × author_ss:"Zhang, Y."
  1. Zhang, Y.; Zhang, G.; Zhu, D.; Lu, J.: Scientific evolutionary pathways : identifying and visualizing relationships for scientific topics (2017) 0.04
    0.04286651 = product of:
      0.08573302 = sum of:
        0.005885557 = product of:
          0.023542227 = sum of:
            0.023542227 = weight(_text_:based in 3758) [ClassicSimilarity], result of:
              0.023542227 = score(doc=3758,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.16644597 = fieldWeight in 3758, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3758)
          0.25 = coord(1/4)
        0.07984746 = weight(_text_:term in 3758) [ClassicSimilarity], result of:
          0.07984746 = score(doc=3758,freq=4.0), product of:
            0.21904005 = queryWeight, product of:
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.04694356 = queryNorm
            0.3645336 = fieldWeight in 3758, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3758)
      0.5 = coord(2/4)
    
    Abstract
    Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.
  2. Zhang, Y.: Understanding the sustained use of online health communities from a self-determination perspective (2016) 0.03
    0.031173116 = product of:
      0.06234623 = sum of:
        0.005885557 = product of:
          0.023542227 = sum of:
            0.023542227 = weight(_text_:based in 3216) [ClassicSimilarity], result of:
              0.023542227 = score(doc=3216,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.16644597 = fieldWeight in 3216, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3216)
          0.25 = coord(1/4)
        0.056460675 = weight(_text_:term in 3216) [ClassicSimilarity], result of:
          0.056460675 = score(doc=3216,freq=2.0), product of:
            0.21904005 = queryWeight, product of:
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.04694356 = queryNorm
            0.25776416 = fieldWeight in 3216, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3216)
      0.5 = coord(2/4)
    
    Abstract
    Sustained use of an information source is sometimes important for achieving an individual's long-term goals, such as learning and self-development. It is even more important for users of online health communities because health benefits usually come with sustained use. However, little is known about what retains a user. We interviewed 21 participants who had been using online diabetes communities in a sustained manner. Guided by self-determination theory, which posits that behaviors are sustained when they can satisfy basic human needs for autonomy, competence, and relatedness, we identified mechanisms that help satisfy these needs, and thus sustain users in online health communities. Autonomy-supportive mechanisms include being respected and supported as a unique individual, feeling free in making choices, and receiving meaningful rationales about others' decisions. Competence-cultivating mechanisms include seeking information, providing information, and exchanging information with others to construct knowledge. Mechanisms that cultivate relatedness include seeing similarities between oneself and peers, receiving responses from others, providing emotional support, and forming small underground groups for closer interactions. The results suggest that, like emotions, information and small group interactions also play a key role in retaining users. System design and community management strategies are discussed based on these mechanisms.
  3. 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) 0.03
    0.027946608 = product of:
      0.11178643 = sum of:
        0.11178643 = weight(_text_:term in 32) [ClassicSimilarity], result of:
          0.11178643 = score(doc=32,freq=4.0), product of:
            0.21904005 = queryWeight, product of:
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.04694356 = queryNorm
            0.510347 = fieldWeight in 32, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.0546875 = fieldNorm(doc=32)
      0.25 = coord(1/4)
    
    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.
  4. Trace, C.B.; Zhang, Y.; Yi, S.; Williams-Brown, M.Y.: Information practices around genetic testing for ovarian cancer patients (2023) 0.02
    0.022704724 = product of:
      0.04540945 = sum of:
        0.005885557 = product of:
          0.023542227 = sum of:
            0.023542227 = weight(_text_:based in 1071) [ClassicSimilarity], result of:
              0.023542227 = score(doc=1071,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.16644597 = fieldWeight in 1071, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1071)
          0.25 = coord(1/4)
        0.039523892 = product of:
          0.079047784 = sum of:
            0.079047784 = weight(_text_:assessment in 1071) [ClassicSimilarity], result of:
              0.079047784 = score(doc=1071,freq=2.0), product of:
                0.25917634 = queryWeight, product of:
                  5.52102 = idf(docFreq=480, maxDocs=44218)
                  0.04694356 = queryNorm
                0.30499613 = fieldWeight in 1071, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  5.52102 = idf(docFreq=480, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1071)
          0.5 = coord(1/2)
      0.5 = coord(2/4)
    
    Abstract
    Knowledge of ovarian cancer patients' information practices around cancer genetic testing (GT) is needed to inform interventions that promote patient access to GT-related information. We interviewed 21 ovarian cancer patients and survivors who had GT as part of the treatment process and analyzed the transcripts using the qualitative content analysis method. We found that patients' information practices, manifested in their information-seeking mode, information sources utilized, information assessment, and information use, showed three distinct styles: passive, semi-active, and active. Patients with the passive style primarily received information from clinical sources, encountered information, or delegated information-seeking to family members; they were not inclined to assess information themselves and seldom used it to learn or influence others. Women with semi-active and active styles adopted more active information-seeking modes to approach information, utilized information sources beyond clinical settings, attempted to assess the information found, and actively used it to learn, educate others, or advocate GT to family and friends. Guided by the social ecological model, we found multiple levels of influences, including personal, interpersonal, organizational, community, and societal, acting as motivators or barriers to patients' information practice. Based on these findings, we discussed strategies to promote patient access to GT-related information.
  5. Zhang, Y.; Kudva, S.: E-books versus print books : readers' choices and preferences across contexts (2014) 0.02
    0.022482082 = product of:
      0.08992833 = sum of:
        0.08992833 = weight(_text_:frequency in 1335) [ClassicSimilarity], result of:
          0.08992833 = score(doc=1335,freq=2.0), product of:
            0.27643865 = queryWeight, product of:
              5.888745 = idf(docFreq=332, maxDocs=44218)
              0.04694356 = queryNorm
            0.32531026 = fieldWeight in 1335, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.888745 = idf(docFreq=332, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1335)
      0.25 = coord(1/4)
    
    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.
  6. 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) 0.02
    0.016340401 = product of:
      0.032680802 = sum of:
        0.010194084 = product of:
          0.040776335 = sum of:
            0.040776335 = weight(_text_:based in 2808) [ClassicSimilarity], result of:
              0.040776335 = score(doc=2808,freq=6.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.28829288 = fieldWeight in 2808, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2808)
          0.25 = coord(1/4)
        0.022486717 = product of:
          0.044973433 = sum of:
            0.044973433 = weight(_text_:22 in 2808) [ClassicSimilarity], result of:
              0.044973433 = score(doc=2808,freq=4.0), product of:
                0.16438834 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04694356 = queryNorm
                0.27358043 = fieldWeight in 2808, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2808)
          0.5 = coord(1/2)
      0.5 = coord(2/4)
    
    Abstract
    Internet based electronic resources are growing dramatically but there have been no empirical studies evaluating the impact of e-sources, as a whole, on formal scholarly communication. reports results of an investigation into how much e-sources have been used in formal scholarly communication, using a case study in the area of Library and Information Science (LIS) during the period 1994 to 1996. 4 citation based indicators were used in the study of the impact measurement. Concludes that, compared with the impact of print sources, the impact of e-sources on formal scholarly communication in LIS is small, as measured by e-sources cited, and does not increase significantly by year even though there is observable growth of these impact across the years. It is found that periodical format is related to the rate of citing e-sources, articles are more likely to cite e-sources than are print priodical articles. However, once authors cite electronic resource, there is no significant difference in the number of references per article by periodical format or by year. Suggests that, at this stage, citing e-sources may depend on authors rather than the periodical format in which authors choose to publish
    Date
    30. 1.1999 17:22:22
  7. Zhang, Y.; Zheng, G.; Yan, H.: Bridging information and communication technology and older adults by social network : an action research in Sichuan, China (2023) 0.01
    0.014115169 = product of:
      0.056460675 = sum of:
        0.056460675 = weight(_text_:term in 1089) [ClassicSimilarity], result of:
          0.056460675 = score(doc=1089,freq=2.0), product of:
            0.21904005 = queryWeight, product of:
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.04694356 = queryNorm
            0.25776416 = fieldWeight in 1089, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.66603 = idf(docFreq=1130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1089)
      0.25 = coord(1/4)
    
    Abstract
    The extant literature demonstrates that the age-related digital divide prevents older adults from enhancing their quality of life. To bridge this gap and promote active aging, this study explores the interplay between social networks and older adults' use of information and communication technology (ICT). Using an action-oriented field research approach, we offered technical help (29 help sessions) to older adult participants recruited from western China. Then, we conducted content analysis to examine the obtained video, audio, and text data. Our results show that, first, different types of social networks significantly influence older adults' ICT use in terms of digital skills, engagement, and attitudes; however, these effects vary from person to person. In particular, our results highlight the crucial role of a stable and long-term supportive social network in learning and mastering ICT for older residents. Second, technical help facilitates the building and reinforcing of such a social network for the participants. Our study has strong implications in that policymakers can foster the digital inclusion of older people through supportive social networks.
  8. 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) 0.01
    0.012111973 = product of:
      0.024223946 = sum of:
        0.008323434 = product of:
          0.033293735 = sum of:
            0.033293735 = weight(_text_:based in 993) [ClassicSimilarity], result of:
              0.033293735 = score(doc=993,freq=4.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.23539014 = fieldWeight in 993, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=993)
          0.25 = coord(1/4)
        0.015900511 = product of:
          0.031801023 = sum of:
            0.031801023 = weight(_text_:22 in 993) [ClassicSimilarity], result of:
              0.031801023 = score(doc=993,freq=2.0), product of:
                0.16438834 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19345059 = fieldWeight in 993, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=993)
          0.5 = coord(1/2)
      0.5 = coord(2/4)
    
    Abstract
    Evaluating the quality of online health information (OHI) is a major challenge facing consumers. We designed PageGraph, an interface that displays quality indicators and associated values for a webpage, based on credibility evaluation models, the nudge theory, and existing empirical research concerning professionals' and consumers' evaluation of OHI quality. A qualitative evaluation of the interface with 16 participants revealed that PageGraph rendered the information and presentation nudges as intended. It provided the participants with easier access to quality indicators, encouraged fresh angles to assess information credibility, provided an evaluation framework, and encouraged validation of initial judgments. We then conducted a quantitative evaluation of the interface involving 60 participants using a between-subject experimental design. The control group used a regular web browser and evaluated the credibility of 12 preselected webpages, whereas the experimental group evaluated the same webpages with the assistance of PageGraph. PageGraph did not significantly influence participants' evaluation results. The results may be attributed to the insufficiency of the saliency and structure of the nudges implemented and the webpage stimuli's lack of sensitivity to the intervention. Future directions for applying nudges to support OHI evaluation were discussed.
    Date
    22. 6.2023 18:18:34
  9. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.01
    0.012111973 = product of:
      0.024223946 = sum of:
        0.008323434 = product of:
          0.033293735 = sum of:
            0.033293735 = weight(_text_:based in 994) [ClassicSimilarity], result of:
              0.033293735 = score(doc=994,freq=4.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.23539014 = fieldWeight in 994, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=994)
          0.25 = coord(1/4)
        0.015900511 = product of:
          0.031801023 = sum of:
            0.031801023 = weight(_text_:22 in 994) [ClassicSimilarity], result of:
              0.031801023 = score(doc=994,freq=2.0), product of:
                0.16438834 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19345059 = fieldWeight in 994, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=994)
          0.5 = coord(1/2)
      0.5 = coord(2/4)
    
    Abstract
    Predicting a researcher's knowledge trajectories beyond their current foci can leverage potential inter-/cross-/multi-disciplinary interactions to achieve exploratory innovation. In this study, we present a method of diffusion-based network analytics for knowledge trajectory recommendation. The method begins by constructing a heterogeneous bibliometric network consisting of a co-topic layer and a co-authorship layer. A novel link prediction approach with a diffusion strategy is then used to capture the interactions between social elements (e.g., collaboration) and knowledge elements (e.g., technological similarity) in the process of exploratory innovation. This diffusion strategy differentiates the interactions occurring among homogeneous and heterogeneous nodes in the heterogeneous bibliometric network and weights the strengths of these interactions. Two sets of experiments-one with a local dataset and the other with a global dataset-demonstrate that the proposed method is prior to 10 selected baselines in link prediction, recommender systems, and upstream graph representation learning. A case study recommending knowledge trajectories of information scientists with topical hierarchy and explainable mediators reveals the proposed method's reliability and potential practical uses in broad scenarios.
    Date
    22. 6.2023 18:07:12
  10. Zhang, Y.; Salaba, A.: What do users tell us about FRBR-based catalogs? (2012) 0.01
    0.005045814 = product of:
      0.020183256 = sum of:
        0.020183256 = product of:
          0.08073302 = sum of:
            0.08073302 = weight(_text_:based in 1924) [ClassicSimilarity], result of:
              0.08073302 = score(doc=1924,freq=12.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.57079077 = fieldWeight in 1924, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1924)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    FRBR user research has been the least addressed area in FRBR research and development. This article addresses the research gap in evaluating and designing catalogs based on FRBR user research. It draws from three user studies concerning FRBR-based catalogs: (1) user evaluation of three FRBR-based catalogs, (2) user participatory design of a prototype catalog based on the FRBR model, and (3) user evaluation of the resulting FRBR prototype catalog. The major findings from the user studies are highlighted and discussed for future development of FRBR-based catalogs that support various user tasks.
  11. Zhang, Y.: Developing a holistic model for digital library evaluation (2010) 0.00
    0.0047701527 = product of:
      0.019080611 = sum of:
        0.019080611 = product of:
          0.038161222 = sum of:
            0.038161222 = weight(_text_:22 in 2360) [ClassicSimilarity], result of:
              0.038161222 = score(doc=2360,freq=2.0), product of:
                0.16438834 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04694356 = queryNorm
                0.23214069 = fieldWeight in 2360, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2360)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    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.
  12. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.00
    0.0047701527 = product of:
      0.019080611 = sum of:
        0.019080611 = product of:
          0.038161222 = sum of:
            0.038161222 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
              0.038161222 = score(doc=2742,freq=2.0), product of:
                0.16438834 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04694356 = queryNorm
                0.23214069 = fieldWeight in 2742, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2742)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Date
    22. 3.2009 17:49:11
  13. Zhang, X.; Fang, Y.; He, W.; Zhang, Y.; Liu, X.: Epistemic motivation, task reflexivity, and knowledge contribution behavior on team wikis : a cross-level moderation model (2019) 0.00
    0.0024970302 = product of:
      0.009988121 = sum of:
        0.009988121 = product of:
          0.039952483 = sum of:
            0.039952483 = weight(_text_:based in 5245) [ClassicSimilarity], result of:
              0.039952483 = score(doc=5245,freq=4.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.28246817 = fieldWeight in 5245, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5245)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    A cross-level model based on the information processing perspective and trait activation theory was developed and tested in order to investigate the effects of individual-level epistemic motivation and team-level task reflexivity on three different individual contribution behaviors (i.e., adding, deleting, and revising) in the process of knowledge creation on team wikis. Using the Hierarchical Linear Modeling software package and the 2-wave data from 166 individuals in 51 wiki-based teams, we found cross-level interaction effects between individual epistemic motivation and team task reflexivity on different knowledge contribution behaviors on wikis. Epistemic motivation exerted a positive effect on adding, which was strengthened by team task reflexivity. The effect of epistemic motivation on deleting was positive only when task reflexivity was high. In addition, epistemic motivation was strongly positively related to revising, regardless of the level of task reflexivity involved.
  14. Zhang, Y.: Toward a layered model of context for health information searching : an analysis of consumer-generated questions (2013) 0.00
    0.0020808585 = product of:
      0.008323434 = sum of:
        0.008323434 = product of:
          0.033293735 = sum of:
            0.033293735 = weight(_text_:based in 953) [ClassicSimilarity], result of:
              0.033293735 = score(doc=953,freq=4.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.23539014 = fieldWeight in 953, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=953)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    Designing effective consumer health information systems requires deep understanding of the context in which the systems are being used. However, due to the elusive nature of the concept of context, few studies have made it a focus of examination. To fill this gap, we studied the context of consumer health information searching by analyzing questions posted on a social question and answer site: Yahoo! Answers. Based on the analysis, a model of context was developed. The model consists of 5 layers: demographic, cognitive, affective, situational, and social and environmental. The demographic layer contains demographic factors of the person of concern; the cognitive layer contains factors related to the current search task (specifically, topics of interest and information goals) and users' cognitive ability to articulate their needs. The affective layer contains different affective motivations and intentions behind the search. The situational layer contains users' perceptions of the current health condition and where the person is in the illness trajectory. The social and environmental layer contains users' social roles, social norms, and various information channels. Several novel system functions, including faceted search and layered presentation of results, are proposed based on the model to help contextualize and improve users' interactions with health information systems.
  15. Zhang, Y.: ¬The effect of open access on citation impact : a comparison study based on Web citation analysis (2006) 0.00
    0.0020808585 = product of:
      0.008323434 = sum of:
        0.008323434 = product of:
          0.033293735 = sum of:
            0.033293735 = weight(_text_:based in 5071) [ClassicSimilarity], result of:
              0.033293735 = score(doc=5071,freq=4.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.23539014 = fieldWeight in 5071, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5071)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    The academic impact advantage of Open Access (OA) is a prominent topic of debate in the library and publishing communities. Web citations have been proposed as comparable to, even replacements for, bibliographic citations in assessing the academic impact of journals. In our study, we compare Web citations to articles in an OA journal, the Journal of Computer-Mediated Communication (JCMC), and a traditional access journal, New Media & Society (NMS), in the communication discipline. Web citation counts for JCMC are significantly higher than those for NMS. Furthermore, JCMC receives significantly higher Web citations from the formal scholarly publications posted on the Web than NMS does. The types of Web citations for journal articles were also examined. In the Web context, the impact of a journal can be assessed using more than one type of source: citations from scholarly articles, teaching materials and non-authoritative documents. The OA journal has higher percentages of citations from the third type, which suggests that, in addition to the research community, the impact advantage of open access is also detectable among ordinary users participating in Web-based academic communication. Moreover, our study also proves that the OA journal has impact advantage in developing countries. Compared with NMS, JCMC has more Web citations from developing countries.
  16. Zhang, Y.: Scholarly use of Internet-based electronic resources (2001) 0.00
    0.0017656671 = product of:
      0.0070626684 = sum of:
        0.0070626684 = product of:
          0.028250674 = sum of:
            0.028250674 = weight(_text_:based in 5212) [ClassicSimilarity], result of:
              0.028250674 = score(doc=5212,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19973516 = fieldWeight in 5212, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5212)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
  17. Zhang, Y.; Xu, W.: Fast exact maximum likelihood estimation for mixture of language model (2008) 0.00
    0.0017656671 = product of:
      0.0070626684 = sum of:
        0.0070626684 = product of:
          0.028250674 = sum of:
            0.028250674 = weight(_text_:based in 2082) [ClassicSimilarity], result of:
              0.028250674 = score(doc=2082,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19973516 = fieldWeight in 2082, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2082)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language model of a given document (or document set), and then do retrieval or classification based on this model. A common language modeling approach assumes the data D is generated from a mixture of several language models. The core problem is to find the maximum likelihood estimation of one language model mixture, given the fixed mixture weights and the other language model mixture. The EM algorithm is usually used to find the solution. In this paper, we proof that an exact maximum likelihood estimation of the unknown mixture component exists and can be calculated using the new algorithm we proposed. We further improve the algorithm and provide an efficient algorithm of O(k) complexity to find the exact solution, where k is the number of words occurring at least once in data D. Furthermore, we proof the probabilities of many words are exactly zeros, and the MLE estimation is implemented as a feature selection technique explicitly.
  18. Zhang, Y.: ¬The influence of mental models on undergraduate students' searching behavior on the Web (2008) 0.00
    0.0017656671 = product of:
      0.0070626684 = sum of:
        0.0070626684 = product of:
          0.028250674 = sum of:
            0.028250674 = weight(_text_:based in 2097) [ClassicSimilarity], result of:
              0.028250674 = score(doc=2097,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19973516 = fieldWeight in 2097, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2097)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    This article explores the effects of undergraduate students' mental models of the Web on their online searching behavior. Forty-four undergraduate students, mainly freshmen and sophomores, participated in the study. Subjects' mental models of the Web were treated as equally good styles and operationalized as drawings of their perceptions about the Web. Four types of mental models of the Web were identified based on the drawings and the associated descriptions: technical view, functional view, process view, and connection view. In the study, subjects were required to finish two search tasks. Searching behavior was measured from four aspects: navigation and performance, subjects' feelings about tasks and their own performances, query construction, and search patterns. The four mental model groups showed different navigation and querying behaviors, but the differences were not significant. Subjects' satisfaction with their own performances was found to be significantly correlated with the time to complete the task. The results also showed that the familiarity of the task to subjects had a major effect on their ways to start interaction, query construction, and search patterns.
  19. Zhang, Y.: Complex adaptive filtering user profile using graphical models (2008) 0.00
    0.0017656671 = product of:
      0.0070626684 = sum of:
        0.0070626684 = product of:
          0.028250674 = sum of:
            0.028250674 = weight(_text_:based in 2445) [ClassicSimilarity], result of:
              0.028250674 = score(doc=2445,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19973516 = fieldWeight in 2445, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2445)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    This article explores how to develop complex data driven user models that go beyond the bag of words model and topical relevance. We propose to learn from rich user specific information and to satisfy complex user criteria under the graphical modelling framework. We carried out a user study with a web based personal news filtering system, and collected extensive user information, including explicit user feedback, implicit user feedback and some contextual information. Experimental results on the data set collected demonstrate that the graphical modelling approach helps us to better understand the complex domain. The results also show that the complex data driven user modelling approach can improve the adaptive information filtering performance. We also discuss some practical issues while learning complex user models, including how to handle data noise and the missing data problem.
  20. Zhang, Y.; Li, X.; Fan, W.: User adoption of physician's replies in an online health community : an empirical study (2020) 0.00
    0.0017656671 = product of:
      0.0070626684 = sum of:
        0.0070626684 = product of:
          0.028250674 = sum of:
            0.028250674 = weight(_text_:based in 4) [ClassicSimilarity], result of:
              0.028250674 = score(doc=4,freq=2.0), product of:
                0.14144066 = queryWeight, product of:
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.04694356 = queryNorm
                0.19973516 = fieldWeight in 4, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0129938 = idf(docFreq=5906, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4)
          0.25 = coord(1/4)
      0.25 = coord(1/4)
    
    Abstract
    Online health question-and-answer consultation with physicians is becoming a common phenomenon. However, it is unclear how users identify the most satisfying reply. Based on the dual-process theory of knowledge adoption, we developed a conceptual model and empirical method to study which factors influence adoption of a reply. We extracted 6 variables for argument quality (Ease of understanding, Relevance, Completeness, Objectivity, Timeliness, Structure) and 4 for source credibility (Physician's online experience, Physician's offline expertise, Hospital location, Hospital level). The empirical results indicate that both central and peripheral routes affect user's adoption of a response. Physician's offline expertise negatively affects user's adoption decision, while physician's online experience positively affects it; this effect is positively moderated by user involvement.