Search (44 results, page 1 of 3)

  • × author_ss:"Zhang, Y."
  1. Xu, H.; Bu, Y.; Liu, M.; Zhang, C.; Sun, M.; Zhang, Y.; Meyer, E.; Salas, E.; Ding, Y.: Team power dynamics and team impact : new perspectives on scientific collaboration using career age as a proxy for team power (2022) 0.01
    0.0050502303 = product of:
      0.037035022 = sum of:
        0.00514908 = weight(_text_:in in 663) [ClassicSimilarity], result of:
          0.00514908 = score(doc=663,freq=12.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.18406484 = fieldWeight in 663, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=663)
        0.02145788 = weight(_text_:computer in 663) [ClassicSimilarity], result of:
          0.02145788 = score(doc=663,freq=4.0), product of:
            0.0751567 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.02056547 = queryNorm
            0.28550854 = fieldWeight in 663, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.0390625 = fieldNorm(doc=663)
        0.010428062 = product of:
          0.020856123 = sum of:
            0.020856123 = weight(_text_:science in 663) [ClassicSimilarity], result of:
              0.020856123 = score(doc=663,freq=14.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.38499892 = fieldWeight in 663, product of:
                  3.7416575 = tf(freq=14.0), with freq of:
                    14.0 = termFreq=14.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=663)
          0.5 = coord(1/2)
      0.13636364 = coord(3/22)
    
    Abstract
    Power dynamics influence every aspect of scientific collaboration. Team power dynamics can be measured by team power level and team power hierarchy. Team power level is conceptualized as the average level of the possession of resources, expertise, or decision-making authorities of a team. Team power hierarchy represents the vertical differences of the possessions of resources in a team. In Science of Science, few studies have looked at scientific collaboration from the perspective of team power dynamics. This research examines how team power dynamics affect team impact to fill the research gap. In this research, all coauthors of one publication are treated as one team. Team power level and team power hierarchy of one team are measured by the mean and Gini index of career age of coauthors in this team. Team impact is quantified by citations of a paper authored by this team. By analyzing over 7.7 million teams from Science (e.g., Computer Science, Physics), Social Sciences (e.g., Sociology, Library & Information Science), and Arts & Humanities (e.g., Art), we find that flat team structure is associated with higher team impact, especially when teams have high team power level. These findings have been repeated in all five disciplines except Art, and are consistent in various types of teams from Computer Science including teams from industry or academia, teams with different gender groups, teams with geographical contrast, and teams with distinct size.
    Source
    Journal of the Association for Information Science and Technology. 73(2022) no.10, S.1489-1505
  2. Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998) 0.00
    0.004082932 = product of:
      0.029941503 = sum of:
        0.0050450475 = weight(_text_:in in 5704) [ClassicSimilarity], result of:
          0.0050450475 = score(doc=5704,freq=8.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.18034597 = fieldWeight in 5704, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.046875 = fieldNorm(doc=5704)
        0.018207615 = weight(_text_:computer in 5704) [ClassicSimilarity], result of:
          0.018207615 = score(doc=5704,freq=2.0), product of:
            0.0751567 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.02056547 = queryNorm
            0.24226204 = fieldWeight in 5704, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.046875 = fieldNorm(doc=5704)
        0.00668884 = product of:
          0.01337768 = sum of:
            0.01337768 = weight(_text_:science in 5704) [ClassicSimilarity], result of:
              0.01337768 = score(doc=5704,freq=4.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.24694869 = fieldWeight in 5704, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5704)
          0.5 = coord(1/2)
      0.13636364 = coord(3/22)
    
    Abstract
    Presents a neural network approach to document semantic indexing. Reports results of a study to apply a Hopfield net algorithm to simulate human associative memory for concept exploration in the domain of computer science and engineering. The INSPEC database, consisting of 320.000 abstracts from leading periodical articles was used as the document test bed. Benchmark tests conformed that 3 parameters: maximum number of activated nodes; maximum allowable error; and maximum number of iterations; were useful in positively influencing network convergence behaviour without negatively impacting central processing unit performance. Another series of benchmark tests was performed to determine the effectiveness of various filtering techniques in reducing the negative impact of noisy input terms. Preliminary user tests conformed expectations that the Hopfield net is potentially useful as an associative memory technique to improve document recall and precision by solving discrepancies between indexer vocabularies and end user vocabularies
    Source
    Journal of information science. 24(1998) no.1, S.3-18
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  3. 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) 0.00
    0.0035379601 = product of:
      0.03891756 = sum of:
        0.005561643 = weight(_text_:in in 2808) [ClassicSimilarity], result of:
          0.005561643 = score(doc=2808,freq=14.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.19881277 = fieldWeight in 2808, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2808)
        0.033355918 = sum of:
          0.013653537 = weight(_text_:science in 2808) [ClassicSimilarity], result of:
            0.013653537 = score(doc=2808,freq=6.0), product of:
              0.0541719 = queryWeight, product of:
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.02056547 = queryNorm
              0.25204095 = fieldWeight in 2808, product of:
                2.4494898 = tf(freq=6.0), with freq of:
                  6.0 = termFreq=6.0
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.0390625 = fieldNorm(doc=2808)
          0.01970238 = weight(_text_:22 in 2808) [ClassicSimilarity], result of:
            0.01970238 = score(doc=2808,freq=4.0), product of:
              0.072016776 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.02056547 = 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)
      0.09090909 = coord(2/22)
    
    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
    Source
    Journal of information science. 24(1998) no.4, S.241-254
  4. Zhang, Y.: Undergraduate students' mental models of the Web as an information retrieval system (2008) 0.00
    0.003179817 = product of:
      0.023318658 = sum of:
        0.0042042066 = weight(_text_:in in 2385) [ClassicSimilarity], result of:
          0.0042042066 = score(doc=2385,freq=8.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.15028831 = fieldWeight in 2385, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2385)
        0.015173013 = weight(_text_:computer in 2385) [ClassicSimilarity], result of:
          0.015173013 = score(doc=2385,freq=2.0), product of:
            0.0751567 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.02056547 = queryNorm
            0.20188503 = fieldWeight in 2385, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2385)
        0.0039414368 = product of:
          0.0078828735 = sum of:
            0.0078828735 = weight(_text_:science in 2385) [ClassicSimilarity], result of:
              0.0078828735 = score(doc=2385,freq=2.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.1455159 = fieldWeight in 2385, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2385)
          0.5 = coord(1/2)
      0.13636364 = coord(3/22)
    
    Abstract
    This study explored undergraduate students' mental models of the Web as an information retrieval system. Mental models play an important role in people's interaction with information systems. Better understanding of people's mental models could inspire better interface design and user instruction. Multiple data-collection methods, including questionnaire, semistructured interview, drawing, and participant observation, were used to elicit students' mental models of the Web from different perspectives, though only data from interviews and drawing descriptions are reported in this article. Content analysis of the transcripts showed that students had utilitarian rather than structural mental models of the Web. The majority of participants saw the Web as a huge information resource where everything can be found rather than an infrastructure consisting of hardware and computer applications. Students had different mental models of how information is organized on the Web, and the models varied in correctness and complexity. Students' mental models of search on the Web were illustrated from three points of view: avenues of getting information, understanding of search engines' working mechanisms, and search tactics. The research results suggest that there are mainly three sources contributing to the construction of mental models: personal observation, communication with others, and class instruction. In addition to structural and functional aspects, mental models have an emotional dimension.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2087-2098
  5. Zhang, Y.; Wu, D.; Hagen, L.; Song, I.-Y.; Mostafa, J.; Oh, S.; Anderson, T.; Shah, C.; Bishop, B.W.; Hopfgartner, F.; Eckert, K.; Federer, L.; Saltz, J.S.: Data science curriculum in the iField (2023) 0.00
    0.0030202782 = product of:
      0.022148706 = sum of:
        0.0070290747 = product of:
          0.014058149 = sum of:
            0.014058149 = weight(_text_:29 in 964) [ClassicSimilarity], result of:
              0.014058149 = score(doc=964,freq=2.0), product of:
                0.072342895 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.02056547 = queryNorm
                0.19432661 = fieldWeight in 964, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=964)
          0.5 = coord(1/2)
        0.0063063093 = weight(_text_:in in 964) [ClassicSimilarity], result of:
          0.0063063093 = score(doc=964,freq=18.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.22543246 = fieldWeight in 964, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=964)
        0.008813321 = product of:
          0.017626641 = sum of:
            0.017626641 = weight(_text_:science in 964) [ClassicSimilarity], result of:
              0.017626641 = score(doc=964,freq=10.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.32538348 = fieldWeight in 964, product of:
                  3.1622777 = tf(freq=10.0), with freq of:
                    10.0 = termFreq=10.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=964)
          0.5 = coord(1/2)
      0.13636364 = coord(3/22)
    
    Abstract
    Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.
    Date
    12. 5.2023 14:29:42
    Footnote
    Beitrag in einem Special issue on "Data Science in the iField".
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.6, S.641-662
  6. Zhang, Y.: Developing a holistic model for digital library evaluation (2010) 0.00
    0.0028925461 = product of:
      0.031818006 = sum of:
        0.005640535 = weight(_text_:in in 2360) [ClassicSimilarity], result of:
          0.005640535 = score(doc=2360,freq=10.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.20163295 = fieldWeight in 2360, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.046875 = fieldNorm(doc=2360)
        0.026177472 = sum of:
          0.009459447 = weight(_text_:science in 2360) [ClassicSimilarity], result of:
            0.009459447 = score(doc=2360,freq=2.0), product of:
              0.0541719 = queryWeight, product of:
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.02056547 = queryNorm
              0.17461908 = fieldWeight in 2360, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.046875 = fieldNorm(doc=2360)
          0.016718024 = weight(_text_:22 in 2360) [ClassicSimilarity], result of:
            0.016718024 = score(doc=2360,freq=2.0), product of:
              0.072016776 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.02056547 = 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)
      0.09090909 = coord(2/22)
    
    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
  7. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.00
    0.0027040783 = product of:
      0.02974486 = sum of:
        0.0035673876 = weight(_text_:in in 2742) [ClassicSimilarity], result of:
          0.0035673876 = score(doc=2742,freq=4.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.12752387 = fieldWeight in 2742, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.046875 = fieldNorm(doc=2742)
        0.026177472 = sum of:
          0.009459447 = weight(_text_:science in 2742) [ClassicSimilarity], result of:
            0.009459447 = score(doc=2742,freq=2.0), product of:
              0.0541719 = queryWeight, product of:
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.02056547 = queryNorm
              0.17461908 = fieldWeight in 2742, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.046875 = fieldNorm(doc=2742)
          0.016718024 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
            0.016718024 = score(doc=2742,freq=2.0), product of:
              0.072016776 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.02056547 = 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)
      0.09090909 = coord(2/22)
    
    Abstract
    In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.
    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
  8. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.00
    0.0024104551 = product of:
      0.026515007 = sum of:
        0.004700446 = weight(_text_:in in 994) [ClassicSimilarity], result of:
          0.004700446 = score(doc=994,freq=10.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.16802745 = fieldWeight in 994, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=994)
        0.02181456 = sum of:
          0.0078828735 = weight(_text_:science in 994) [ClassicSimilarity], result of:
            0.0078828735 = score(doc=994,freq=2.0), product of:
              0.0541719 = queryWeight, product of:
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.02056547 = queryNorm
              0.1455159 = fieldWeight in 994, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.0390625 = fieldNorm(doc=994)
          0.013931687 = weight(_text_:22 in 994) [ClassicSimilarity], result of:
            0.013931687 = score(doc=994,freq=2.0), product of:
              0.072016776 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.02056547 = 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)
      0.09090909 = coord(2/22)
    
    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
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.775-790
  9. Zhang, Y.; Zheng, G.; Yan, H.: Bridging information and communication technology and older adults by social network : an action research in Sichuan, China (2023) 0.00
    0.0021981262 = product of:
      0.016119592 = sum of:
        0.0070290747 = product of:
          0.014058149 = sum of:
            0.014058149 = weight(_text_:29 in 1089) [ClassicSimilarity], result of:
              0.014058149 = score(doc=1089,freq=2.0), product of:
                0.072342895 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.02056547 = queryNorm
                0.19432661 = fieldWeight in 1089, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1089)
          0.5 = coord(1/2)
        0.00514908 = weight(_text_:in in 1089) [ClassicSimilarity], result of:
          0.00514908 = score(doc=1089,freq=12.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.18406484 = fieldWeight in 1089, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1089)
        0.0039414368 = product of:
          0.0078828735 = sum of:
            0.0078828735 = weight(_text_:science in 1089) [ClassicSimilarity], result of:
              0.0078828735 = score(doc=1089,freq=2.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.1455159 = fieldWeight in 1089, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1089)
          0.5 = coord(1/2)
      0.13636364 = coord(3/22)
    
    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.
    Content
    Beitrag in: JASIST special issue on ICT4D and intersections with the information field. Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24700.
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.12, S.1437-1448
  10. Zhang, Y.: ¬The effect of open access on citation impact : a comparison study based on Web citation analysis (2006) 0.00
    0.0019526659 = product of:
      0.021479324 = sum of:
        0.0063063093 = weight(_text_:in in 5071) [ClassicSimilarity], result of:
          0.0063063093 = score(doc=5071,freq=18.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.22543246 = fieldWeight in 5071, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5071)
        0.015173013 = weight(_text_:computer in 5071) [ClassicSimilarity], result of:
          0.015173013 = score(doc=5071,freq=2.0), product of:
            0.0751567 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.02056547 = queryNorm
            0.20188503 = fieldWeight in 5071, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5071)
      0.09090909 = coord(2/22)
    
    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.
  11. Trace, C.B.; Zhang, Y.; Yi, S.; Williams-Brown, M.Y.: Information practices around genetic testing for ovarian cancer patients (2023) 0.00
    0.0017826294 = product of:
      0.0130726155 = sum of:
        0.0070290747 = product of:
          0.014058149 = sum of:
            0.014058149 = weight(_text_:29 in 1071) [ClassicSimilarity], result of:
              0.014058149 = score(doc=1071,freq=2.0), product of:
                0.072342895 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.02056547 = queryNorm
                0.19432661 = fieldWeight in 1071, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1071)
          0.5 = coord(1/2)
        0.0021021033 = weight(_text_:in in 1071) [ClassicSimilarity], result of:
          0.0021021033 = score(doc=1071,freq=2.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.07514416 = fieldWeight in 1071, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1071)
        0.0039414368 = product of:
          0.0078828735 = sum of:
            0.0078828735 = weight(_text_:science in 1071) [ClassicSimilarity], result of:
              0.0078828735 = score(doc=1071,freq=2.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.1455159 = fieldWeight in 1071, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1071)
          0.5 = coord(1/2)
      0.13636364 = coord(3/22)
    
    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.
    Date
    21.10.2023 17:29:59
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.11, S.1265-1281
  12. Shah, C.; Anderson, T.; Hagen, L.; Zhang, Y.: ¬An iSchool approach to data science : human-centered, socially responsible, and context-driven (2021) 0.00
    0.0014161038 = product of:
      0.015577141 = sum of:
        0.00514908 = weight(_text_:in in 244) [ClassicSimilarity], result of:
          0.00514908 = score(doc=244,freq=12.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.18406484 = fieldWeight in 244, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=244)
        0.010428062 = product of:
          0.020856123 = sum of:
            0.020856123 = weight(_text_:science in 244) [ClassicSimilarity], result of:
              0.020856123 = score(doc=244,freq=14.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.38499892 = fieldWeight in 244, product of:
                  3.7416575 = tf(freq=14.0), with freq of:
                    14.0 = termFreq=14.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=244)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    Abstract
    The Information Schools, also referred to as iSchools, have a unique approach to data science with three distinct components: human-centeredness, socially responsible, and rooted in context. In this position paper, we highlight and expand on these components and show how they are integrated in various research and educational activities related to data science that are being carried out at iSchools. We argue that the iSchool way of doing data science is not only highly relevant to the current times, but also crucial in solving problems of tomorrow. Specifically, we accentuate the issues of developing insights and solutions that are not only data-driven, but also incorporate human values, including transparency, privacy, ethics, fairness, and equity. This approach to data science has meaningful implications on how we educate the students and train the next generation of scholars and policymakers. Here, we provide some of those design decisions, rooted in evidence-based research, along with our perspective on how data science is currently situated and how it should be advanced in iSchools.
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.6, S.793-796
  13. Zhang, M.; Zhang, Y.: Professional organizations in Twittersphere : an empirical study of U.S. library and information science professional organizations-related Tweets (2020) 0.00
    0.0013322552 = product of:
      0.014654807 = sum of:
        0.0050973296 = weight(_text_:in in 5775) [ClassicSimilarity], result of:
          0.0050973296 = score(doc=5775,freq=6.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.1822149 = fieldWeight in 5775, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5775)
        0.009557477 = product of:
          0.019114954 = sum of:
            0.019114954 = weight(_text_:science in 5775) [ClassicSimilarity], result of:
              0.019114954 = score(doc=5775,freq=6.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.35285735 = fieldWeight in 5775, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=5775)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.4, S.491-496
  14. 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) 0.00
    0.0013322552 = product of:
      0.014654807 = sum of:
        0.0050973296 = weight(_text_:in in 32) [ClassicSimilarity], result of:
          0.0050973296 = score(doc=32,freq=6.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.1822149 = fieldWeight in 32, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0546875 = fieldNorm(doc=32)
        0.009557477 = product of:
          0.019114954 = sum of:
            0.019114954 = weight(_text_:science in 32) [ClassicSimilarity], result of:
              0.019114954 = score(doc=32,freq=6.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.35285735 = fieldWeight in 32, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=32)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.12, S.1419-1423
  15. Zhang, Y.; Salaba, A.: What do users tell us about FRBR-based catalogs? (2012) 0.00
    0.0012729687 = product of:
      0.014002656 = sum of:
        0.009840704 = product of:
          0.019681407 = sum of:
            0.019681407 = weight(_text_:29 in 1924) [ClassicSimilarity], result of:
              0.019681407 = score(doc=1924,freq=2.0), product of:
                0.072342895 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.02056547 = queryNorm
                0.27205724 = fieldWeight in 1924, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1924)
          0.5 = coord(1/2)
        0.004161952 = weight(_text_:in in 1924) [ClassicSimilarity], result of:
          0.004161952 = score(doc=1924,freq=4.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.14877784 = fieldWeight in 1924, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1924)
      0.09090909 = coord(2/22)
    
    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.
    Date
    29. 5.2015 10:48:25
  16. Zhang, Y.: Scholarly use of Internet-based electronic resources (2001) 0.00
    0.0011208523 = product of:
      0.012329375 = sum of:
        0.005640535 = weight(_text_:in in 5212) [ClassicSimilarity], result of:
          0.005640535 = score(doc=5212,freq=10.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.20163295 = fieldWeight in 5212, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.046875 = fieldNorm(doc=5212)
        0.00668884 = product of:
          0.01337768 = sum of:
            0.01337768 = weight(_text_:science in 5212) [ClassicSimilarity], result of:
              0.01337768 = score(doc=5212,freq=4.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.24694869 = fieldWeight in 5212, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5212)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    Abstract
    By Internet resources Zhang means any electronic file accessible by any Internet protocol. Their usage is determined by an examination of the citations to such sources in a nine-year sample of four print and four electronic LIS journals, by a survey of editors of these journals, and by a survey of scholars with "in press" papers in these journals. Citations were gathered from Social Science Citation Index and manually classed as e-sources by the format used. All authors with "in press" papers were asked about their use and opinion of Internet sources and for any suggestions for improvement. Use of electronic sources is heavy and access is very high. Access and ability explain most usage while satisfaction was not significant. Citation of e-journals increases over the eight years. Authors report under citation of e-journals in favor of print equivalents. Traditional reasons are given for citing and not citing, but additional reasons are also present for e-journals.
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.8, S.628-654
  17. Zhang, Y.; Zhang, G.; Zhu, D.; Lu, J.: Scientific evolutionary pathways : identifying and visualizing relationships for scientific topics (2017) 0.00
    0.0010988256 = product of:
      0.012087081 = sum of:
        0.0042042066 = weight(_text_:in in 3758) [ClassicSimilarity], result of:
          0.0042042066 = score(doc=3758,freq=8.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.15028831 = fieldWeight in 3758, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3758)
        0.0078828735 = product of:
          0.015765747 = sum of:
            0.015765747 = weight(_text_:science in 3758) [ClassicSimilarity], result of:
              0.015765747 = score(doc=3758,freq=8.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.2910318 = fieldWeight in 3758, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3758)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.8, S.1925-1939
  18. 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) 0.00
    9.91571E-4 = product of:
      0.02181456 = sum of:
        0.02181456 = sum of:
          0.0078828735 = weight(_text_:science in 993) [ClassicSimilarity], result of:
            0.0078828735 = score(doc=993,freq=2.0), product of:
              0.0541719 = queryWeight, product of:
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.02056547 = queryNorm
              0.1455159 = fieldWeight in 993, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.6341193 = idf(docFreq=8627, maxDocs=44218)
                0.0390625 = fieldNorm(doc=993)
          0.013931687 = weight(_text_:22 in 993) [ClassicSimilarity], result of:
            0.013931687 = score(doc=993,freq=2.0), product of:
              0.072016776 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.02056547 = 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)
      0.045454547 = coord(1/22)
    
    Date
    22. 6.2023 18:18:34
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.828-845
  19. 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) 0.00
    9.340436E-4 = product of:
      0.010274479 = sum of:
        0.004700446 = weight(_text_:in in 5963) [ClassicSimilarity], result of:
          0.004700446 = score(doc=5963,freq=10.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.16802745 = fieldWeight in 5963, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5963)
        0.005574033 = product of:
          0.011148066 = sum of:
            0.011148066 = weight(_text_:science in 5963) [ClassicSimilarity], result of:
              0.011148066 = score(doc=5963,freq=4.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.20579056 = fieldWeight in 5963, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5963)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.10, S.1162-1178
  20. 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
    8.8861556E-4 = product of:
      0.009774771 = sum of:
        0.0050450475 = weight(_text_:in in 5245) [ClassicSimilarity], result of:
          0.0050450475 = score(doc=5245,freq=8.0), product of:
            0.027974274 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.02056547 = queryNorm
            0.18034597 = fieldWeight in 5245, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.046875 = fieldNorm(doc=5245)
        0.0047297236 = product of:
          0.009459447 = sum of:
            0.009459447 = weight(_text_:science in 5245) [ClassicSimilarity], result of:
              0.009459447 = score(doc=5245,freq=2.0), product of:
                0.0541719 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.02056547 = queryNorm
                0.17461908 = fieldWeight in 5245, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5245)
          0.5 = coord(1/2)
      0.09090909 = coord(2/22)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.5, S.448-461

Years

Types

  • a 43
  • m 1
  • More… Less…

Classifications