Search (5 results, page 1 of 1)

  • × author_ss:"Zhang, X."
  • × year_i:[2020 TO 2030}
  1. Zhang, X.; Wang, D.; Tang, Y.; Xiao, Q.: How question type influences knowledge withholding in social Q&A community (2023) 0.02 
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    Abstract
    Social question-and-answer (Q&A) communities are becoming increasingly important for knowledge acquisition. However, some users withhold knowledge, which can hinder the effectiveness of these platforms. Based on social exchange theory, the study investigates how different types of questions influence knowledge withholding, with question difficulty and user anonymity as boundary conditions. Two experiments were conducted to test hypotheses. Results indicate that informational questions are more likely to lead to knowledge withholding than conversational ones, as they elicit more fear of negative evaluation and fear of exploitation. The study also examines the interplay of question difficulty and user anonymity with question type. Overall, this study significantly extends the existing literature on counterproductive knowledge behavior by exploring the antecedents of knowledge withholding in social Q&A communities.
    Date
    22. 9.2023 13:51:47
    Type
    a
  2. Yang, F.; Zhang, X.: Focal fields in literature on the information divide : the USA, China, UK and India (2020) 0.02 
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    Abstract
    Purpose The purpose of this paper is to identify key countries and their focal research fields on the information divide. Design/methodology/approach Literature was retrieved to identify key countries and their primary focus. The literature research method was adopted to identify aspects of the primary focus in each key country. Findings The key countries with literature on the information divide are the USA, China, the UK and India. The problem of health is prominent in the USA, and solutions include providing information, distinguishing users' profiles and improving eHealth literacy. Economic and political factors led to the urban-rural information divide in China, and policy is the most powerful solution. Under the influence of humanism, research on the information divide in the UK focuses on all age groups, and solutions differ according to age. Deep-rooted patriarchal concepts and traditional marriage customs make the gender information divide prominent in India, and increasing women's information consciousness is a feasible way to reduce this divide. Originality/value This paper is an extensive review study on the information divide, which clarifies the key countries and their focal fields in research on this topic. More important, the paper innovatively analyzes and summarizes existing literature from a country perspective.
    Date
    13. 2.2020 18:22:13
    Type
    a
  3. Cui, Y.; Wang, Y.; Liu, X.; Wang, X.; Zhang, X.: Multidimensional scholarly citations : characterizing and understanding scholars' citation behaviors (2023) 0.00 
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    Abstract
    This study investigates scholars' citation behaviors from a fine-grained perspective. Specifically, each scholarly citation is considered multidimensional rather than logically unidimensional (i.e., present or absent). Thirty million articles from PubMed were accessed for use in empirical research, in which a total of 15 interpretable features of scholarly citations were constructed and grouped into three main categories. Each category corresponds to one aspect of the reasons and motivations behind scholars' citation decision-making during academic writing. Using about 500,000 pairs of actual and randomly generated scholarly citations, a series of Random Forest-based classification experiments were conducted to quantitatively evaluate the correlation between each constructed citation feature and citation decisions made by scholars. Our experimental results indicate that citation proximity is the category most relevant to scholars' citation decision-making, followed by citation authority and citation inertia. However, big-name scholars whose h-indexes rank among the top 1% exhibit a unique pattern of citation behaviors-their citation decision-making correlates most closely with citation inertia, with the correlation nearly three times as strong as that of their ordinary counterparts. Hopefully, the empirical findings presented in this paper can bring us closer to characterizing and understanding the complex process of generating scholarly citations in academia.
    Type
    a
  4. Tay, W.; Zhang, X.; Karimi , S.: Beyond mean rating : probabilistic aggregation of star ratings based on helpfulness (2020) 0.00 
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    Abstract
    The star-rating mechanism of customer reviews is used universally by the online population to compare and select merchants, movies, products, and services. The consensus opinion from aggregation of star ratings is used as a proxy for item quality. Online reviews are noisy and effective aggregation of star ratings to accurately reflect the "true quality" of products and services is challenging. The mean-rating aggregation model is widely used and other aggregation models are also proposed. These existing aggregation models rely on a large number of reviews to tolerate noise. However, many products rarely have reviews. We propose probabilistic aggregation models for review ratings based on the Dirichlet distribution to combat data sparsity in reviews. We further propose to exploit the "helpfulness" social information and time to filter noisy reviews and effectively aggregate ratings to compute the consensus opinion. Our experiments on an Amazon data set show that our probabilistic aggregation models based on "helpfulness" achieve better performance than the statistical and heuristic baseline approaches.
    Type
    a
  5. Wu, M.; Liu, Y.-H.; Brownlee, R.; Zhang, X.: Evaluating utility and automatic classification of subject metadata from Research Data Australia (2021) 0.00 
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    Abstract
    In this paper, we present a case study of how well subject metadata (comprising headings from an international classification scheme) has been deployed in a national data catalogue, and how often data seekers use subject metadata when searching for data. Through an analysis of user search behaviour as recorded in search logs, we find evidence that users utilise the subject metadata for data discovery. Since approximately half of the records ingested by the catalogue did not include subject metadata at the time of harvest, we experimented with automatic subject classification approaches in order to enrich these records and to provide additional support for user search and data discovery. Our results show that automatic methods work well for well represented categories of subject metadata, and these categories tend to have features that can distinguish themselves from the other categories. Our findings raise implications for data catalogue providers; they should invest more effort to enhance the quality of data records by providing an adequate description of these records for under-represented subject categories.
    Type
    a

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