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The development and empirical study of a literature review aiding system

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  • Tsung Teng Chen

    (National Taipei University)

Abstract

Literature review is an important but time-consuming task that involves many disparate steps. A simple query to a library database may return voluminous literature that often bewilders novices.We believe the bibliographic techniques developed by the information scientists provide useful process and methods that facilitate literature analysis and review. We thereby developed a citation-based literature analyzing and structuring system, which may facilitate novices to perform tasks that are usually carried out by trained professionals. A field study was carried out to gauge the utility as well as users’ perception using a questionnaire adopted from relevant empirical studies. Graduate students participated in the field study are able to publish papers in their first semester by utilizing this system. The utility and usefulness of the intellectual structuring system are demonstrated by the objective evidence of the high acceptance rate of papers utilizing the system as well as the subjective positive response from the users. A system utilization model utilizing the structure equation modeling technique found the task characteristics construct affects the information quality construct, which in turn affects the perceive usefulness of the system.

Suggested Citation

  • Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    • Handle: RePEc:spr:scient:v:92:y:2012:i:1:d:10.1007_s11192-012-0728-3
    DOI: 10.1007/s11192-012-0728-3
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    Cited by:

    1. Silva, Filipi N. & Amancio, Diego R. & Bardosova, Maria & Costa, Luciano da F. & Oliveira, Osvaldo N., 2016. "Using network science and text analytics to produce surveys in a scientific topic," Journal of Informetrics, Elsevier, vol. 10(2), pages 487-502.
    2. Jason Portenoy & Jevin D. West, 2020. "Constructing and evaluating automated literature review systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 3233-3251, December.
    3. Benito-Santos, Alejandro & Theron, Roberto, 2019. "Cross-domain Visual Exploration of Academic Corpora via the Latent Meaning of User-authored Keywords," OSF Preprints h29qv, Center for Open Science.

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