Search (15 results, page 1 of 1)

  • × author_ss:"Zhang, Y."
  1. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.01 
    0.012261091 = product of:
  0.07356654 = sum of:
    0.07356654 = sum of:
      0.041830957 = weight(_text_:methods in 2742) [ClassicSimilarity], result of:
        0.041830957 = score(doc=2742,freq=2.0), product of:
          0.15695344 = queryWeight, product of:
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.03903913 = queryNorm
          0.26651827 = fieldWeight in 2742, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.046875 = fieldNorm(doc=2742)
      0.03173558 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
        0.03173558 = score(doc=2742,freq=2.0), product of:
          0.1367084 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.03903913 = 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)
  0.16666667 = coord(1/6)
    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
  2. 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 
    0.010623204 = product of:
  0.03186961 = sum of:
    0.018646449 = product of:
      0.037292898 = sum of:
        0.037292898 = weight(_text_:theory in 993) [ClassicSimilarity], result of:
          0.037292898 = score(doc=993,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.2297209 = fieldWeight in 993, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0390625 = fieldNorm(doc=993)
      0.5 = coord(1/2)
    0.013223159 = product of:
      0.026446318 = sum of:
        0.026446318 = weight(_text_:22 in 993) [ClassicSimilarity], result of:
          0.026446318 = score(doc=993,freq=2.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = 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)
  0.33333334 = coord(2/6)
    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
  3. 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 
    0.0037292899 = product of:
  0.022375738 = sum of:
    0.022375738 = product of:
      0.044751476 = sum of:
        0.044751476 = weight(_text_:theory in 5245) [ClassicSimilarity], result of:
          0.044751476 = score(doc=5245,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.27566507 = fieldWeight in 5245, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.046875 = fieldNorm(doc=5245)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    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.
  4. Zhang, Y.; Li, X.; Fan, W.: User adoption of physician's replies in an online health community : an empirical study (2020) 0.00 
    0.0037292899 = product of:
  0.022375738 = sum of:
    0.022375738 = product of:
      0.044751476 = sum of:
        0.044751476 = weight(_text_:theory in 4) [ClassicSimilarity], result of:
          0.044751476 = score(doc=4,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.27566507 = fieldWeight in 4, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.046875 = fieldNorm(doc=4)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    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.
  5. Zhang, Y.; Ren, P.; Rijke, M. de: ¬A taxonomy, data set, and benchmark for detecting and classifying malevolent dialogue responses (2021) 0.00 
    0.0034859132 = product of:
  0.020915478 = sum of:
    0.020915478 = product of:
      0.041830957 = sum of:
        0.041830957 = weight(_text_:methods in 356) [ClassicSimilarity], result of:
          0.041830957 = score(doc=356,freq=2.0), product of:
            0.15695344 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.03903913 = queryNorm
            0.26651827 = fieldWeight in 356, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.046875 = fieldNorm(doc=356)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    Abstract
    Conversational interfaces are increasingly popular as a way of connecting people to information. With the increased generative capacity of corpus-based conversational agents comes the need to classify and filter out malevolent responses that are inappropriate in terms of content and dialogue acts. Previous studies on the topic of detecting and classifying inappropriate content are mostly focused on a specific category of malevolence or on single sentences instead of an entire dialogue. We make three contributions to advance research on the malevolent dialogue response detection and classification (MDRDC) task. First, we define the task and present a hierarchical malevolent dialogue taxonomy. Second, we create a labeled multiturn dialogue data set and formulate the MDRDC task as a hierarchical classification task. Last, we apply state-of-the-art text classification methods to the MDRDC task, and report on experiments aimed at assessing the performance of these approaches.
  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) 0.00 
    0.0031167285 = product of:
  0.01870037 = sum of:
    0.01870037 = product of:
      0.03740074 = sum of:
        0.03740074 = weight(_text_:22 in 2808) [ClassicSimilarity], result of:
          0.03740074 = score(doc=2808,freq=4.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    Date
    30. 1.1999 17:22:22
  7. Zhang, Y.; Salaba, A.: What do users tell us about FRBR-based catalogs? (2012) 0.00 
    0.003113411 = product of:
  0.018680464 = sum of:
    0.018680464 = product of:
      0.03736093 = sum of:
        0.03736093 = weight(_text_:29 in 1924) [ClassicSimilarity], result of:
          0.03736093 = score(doc=1924,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    Date
    29. 5.2015 10:48:25
  8. Zhang, Y.: Understanding the sustained use of online health communities from a self-determination perspective (2016) 0.00 
    0.0031077415 = product of:
  0.018646449 = sum of:
    0.018646449 = product of:
      0.037292898 = sum of:
        0.037292898 = weight(_text_:theory in 3216) [ClassicSimilarity], result of:
          0.037292898 = score(doc=3216,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.2297209 = fieldWeight in 3216, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3216)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    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.
  9. Tenopir, C.; Wang, P.; Zhang, Y.; Simmons, B.; Pollard, R.: Academic users' interactions with ScienceDirect in search tasks : affective and cognitive behaviors (2008) 0.00 
    0.0029049278 = product of:
  0.017429566 = sum of:
    0.017429566 = product of:
      0.034859132 = sum of:
        0.034859132 = weight(_text_:methods in 2027) [ClassicSimilarity], result of:
          0.034859132 = score(doc=2027,freq=2.0), product of:
            0.15695344 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.03903913 = queryNorm
            0.22209854 = fieldWeight in 2027, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2027)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    Abstract
    This article presents part of phase 2 of a research project funded by the NSF-National Science Digital Library Project, which observed how academic users interact with the ScienceDirect information retrieval system for simulated class-related assignments. The ultimate goal of the project is twofold: (1) to find ways to improve science and engineering students' use of science e-journal systems; (2) to develop methods to measure user interaction behaviors. Process-tracing technique recorded participants' processes and interaction behaviors that are measurable; think-aloud protocol captured participants' affective and cognitive verbalizations; pre- and post-search questionnaires solicited demographic information, prior experience with the system, and comments. We explored possible relationships between affective feelings and cognitive behaviors. During search interactions both feelings and thoughts occurred frequently. Positive feelings were more common and were associated more often with thoughts about results. Negative feelings were associated more often with thoughts related to the system, search strategy, and task. Learning styles are also examined as a factor influencing behavior. Engineering graduate students with an assimilating learning style searched longer and paused less than those with a converging learning style. Further exploration of learning styles is suggested.
  10. Zhang, Y.: Undergraduate students' mental models of the Web as an information retrieval system (2008) 0.00 
    0.0029049278 = product of:
  0.017429566 = sum of:
    0.017429566 = product of:
      0.034859132 = sum of:
        0.034859132 = weight(_text_:methods in 2385) [ClassicSimilarity], result of:
          0.034859132 = score(doc=2385,freq=2.0), product of:
            0.15695344 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.03903913 = queryNorm
            0.22209854 = fieldWeight in 2385, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2385)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    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.
  11. Zhang, Y.: Developing a holistic model for digital library evaluation (2010) 0.00 
    0.0026446318 = product of:
  0.01586779 = sum of:
    0.01586779 = product of:
      0.03173558 = sum of:
        0.03173558 = weight(_text_:22 in 2360) [ClassicSimilarity], result of:
          0.03173558 = score(doc=2360,freq=2.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    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.; 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 
    0.0022238651 = product of:
  0.01334319 = sum of:
    0.01334319 = product of:
      0.02668638 = sum of:
        0.02668638 = weight(_text_:29 in 964) [ClassicSimilarity], result of:
          0.02668638 = score(doc=964,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    Date
    12. 5.2023 14:29:42
  13. Trace, C.B.; Zhang, Y.; Yi, S.; Williams-Brown, M.Y.: Information practices around genetic testing for ovarian cancer patients (2023) 0.00 
    0.0022238651 = product of:
  0.01334319 = sum of:
    0.01334319 = product of:
      0.02668638 = sum of:
        0.02668638 = weight(_text_:29 in 1071) [ClassicSimilarity], result of:
          0.02668638 = score(doc=1071,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    Date
    21.10.2023 17:29:59
  14. 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 
    0.0022238651 = product of:
  0.01334319 = sum of:
    0.01334319 = product of:
      0.02668638 = sum of:
        0.02668638 = weight(_text_:29 in 1089) [ClassicSimilarity], result of:
          0.02668638 = score(doc=1089,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    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.
  15. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.00 
    0.0022038599 = product of:
  0.013223159 = sum of:
    0.013223159 = product of:
      0.026446318 = sum of:
        0.026446318 = weight(_text_:22 in 994) [ClassicSimilarity], result of:
          0.026446318 = score(doc=994,freq=2.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = 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)
  0.16666667 = coord(1/6)
    Date
    22. 6.2023 18:07:12

Authors

Years

Themes