Search (6 results, page 1 of 1)

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Abstract

Knowledge withholding, which is defined as the likelihood that an individual devotes less than full effort to knowledge contribution, can be regarded as an emerging social deviance behavior for knowledge practice in online knowledge spaces. However, prior studies placed a great emphasis on proactive knowledge behaviors, such as knowledge sharing and contribution, but failed to consider the uniqueness of knowledge withholding. To capture the social-deviant nature of knowledge withholding and to better understand how people deal with counterproductive knowledge behaviors, this study develops a research model based on the secondary control perspective. Empirical analyses were conducted using the data collected from an online knowledge space. The results indicate that both predictive control and vicarious control exert a positive influence on knowledge withholding. This study also incorporates knowledge-withholding acceptability as a moderating variable of secondary control strategies. In particular, knowledge-withholding acceptability enhances the impact of predictive control, whereas it weakens the effect of vicarious control on knowledge withholding. This study concludes with a discussion of the key findings, and the implications for both research and practice.

Footnote

Beitrag eines Special issue on social informatics of knowledge

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Abstract

To advance the theoretical understanding on information adoption, this study tries to extend the information adoption model (IAM) in three ways. First, this study considers the relationship between source credibility and argument quality and the relationship between herding factors and information usefulness (i.e., bias effects). Second, this study proposes the interaction effects of source credibility and argument quality and the interaction effects of herding factors and information usefulness (i.e., synergistic effects). Third, this study explores the moderating role of an information characteristic - search versus experience information (i.e., information contingency effects). The proposed extended information adoption model (EIAM) is empirically tested through a 2 by 2 by 2 experiment in the social Q&A context, and the results confirm most of the hypotheses. Finally, theoretical contributions and practical implications are discussed.

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Abstract

The quality of online health information for consumers has been a critical issue that concerns all stakeholders in healthcare. To gain an understanding of how quality is evaluated, this systematic review examined 165 articles in which researchers evaluated the quality of consumer-oriented health information on the web against predefined criteria. It was found that studies typically evaluated quality in relation to the substance and formality of content, as well as to the design of technological platforms. Attention to design, particularly interactivity, privacy, and social and cultural appropriateness is on the rise, which suggests the permeation of a user-centered perspective into the evaluation of health information systems, and a growing recognition of the need to study these systems from a social-technical perspective. Researchers used many preexisting instruments to facilitate evaluation of the formality of content; however, only a few were used in multiple studies, and their validity was questioned. The quality of content (i.e., accuracy and completeness) was always evaluated using proprietary instruments constructed based on medical guidelines or textbooks. The evaluation results revealed that the quality of health information varied across medical domains and across websites, and that the overall quality remained problematic. Future research is needed to examine the quality of user-generated content and to explore opportunities offered by emerging new media that can facilitate the consumer evaluation of health information.

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Abstract

Topic discovery is an important means for marketing, e-Business and social science studies. As well, it can be applied to various purposes, such as identifying a group with certain properties and observing the emergence and diminishment of a certain cyber community. Previous topic discovery work (J.M. Kleinberg, Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms, San Francisco, California, p. 668) requires manual judgment of usefulness of outcomes and is thus incapable of handling the explosive growth of the Internet. In this paper, we propose the Automatic Topic Discovery (ATD) method, which combines a method of base set construction, a clustering algorithm and an iterative principal eigenvector computation method to discover the topics relevant to a given query without using manual examination. Given a query, ATD returns with topics associated with the query and top representative pages for each topic. Our experiments show that the ATD method performs better than the traditional eigenvector method in terms of computation time and topic discovery quality.

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Abstract

The information schools, also referred to as iField schools, are leaders in data science education. This study aims to develop a data science graduate curriculum model from an information science perspective to support iField schools in developing data science graduate education. In June 2020, information about 96 data science graduate programs from iField schools worldwide was collected and analyzed using a mixed research method based on inductive content analysis. A wide range of data science competencies and skills development and 12 knowledge topics covered by the curriculum were obtained. The humanistic model is further taken as the theoretical and methodological basis for course model construction, and 12 course knowledge topics are reconstructed into 4 course modules, including (a) data-driven methods and techniques; (b) domain knowledge; (c) legal, moral, and ethical aspects of data; and (d) shaping and developing personal traits, and human-centered data science graduate curriculum model is formed. At the end of the study, the wide application prospect of this model is discussed.

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Date

22. 3.2009 19:07:20