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Scholarly Output Graph: A Graphical Article-Level Metric Indicating the Impact of a Scholar’s Publications

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Advanced Data Mining and Applications (ADMA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10086))

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Abstract

Statistically, top scholars tend to accumulate a large number of publications during their tenure. While the patterns illustrating their scientific impact are monotonous and it is difficult to get a concrete comprehension to the academic development of the scholars’ output. So we address the issue of graphically presenting and comparing the impact of individual scholars’ publications. Besides, with the development of Web 2.0, more information about the social impact of a scholar’s work is becoming increasingly available and relevant. Thus comes the challenge of how to quickly compare among a scholar’s entire collection of publications, and pinpoint those with higher social popularity as well as academic influence. To this end, we propose a graphical article-level metric, namely Scholarly Output Graph (SOG). SOG captures three dimensions including journal impact factor (JIF), scientific impact and social popularity, and reflects not only the quality of the publications but also the immediate responses from social networks. With the visual cues of block length, width and color, users can intuitively locate articles of higher scientific impact, JIF and social popularity. Additionally, SOG proves to be widely applicable, practical and flexible as a navigation tool for filtering publications. To demonstrate the usability of SOG, we design a literature navigation homepage with a list of 50 researchers in computer science with their individual scholarly output graphs and the results can be found at http://impact.linkscholar.org/SOGExample.html.

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Acknowledgements

This work was supported in part by the Natural Science Foundation of China grant 61300087,61502069, 61672128; the Natural Science Foundation of Liaoning grant 2015020003; and by the Fundamental Research Funds for the Central Universities grant DUT15QY40, DUT16ZD(G)02.

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Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, 116620, China

    Yu Liu, Dan Lin, Jing Li & Shimin Shan

  2. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, 116620, China

    Yu Liu, Dan Lin, Jing Li & Shimin Shan

Authors
  1. Yu Liu
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  2. Dan Lin
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  3. Jing Li
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  4. Shimin Shan
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Corresponding author

Correspondence to Yu Liu .

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Editors and Affiliations

  1. University of Technology , Sydney, New South Wales, Australia

    Jinyan Li

  2. University of Queensland , Brisbane, Australia

    Xue Li

  3. Beijing Institute of Technology , Beijing, China

    Shuliang Wang

  4. University of Western Australia , Crawley, West Australia, Australia

    Jianxin Li

  5. University of Adelaide , Adelaide, South Australia, Australia

    Quan Z. Sheng

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Liu, Y., Lin, D., Li, J., Shan, S. (2016). Scholarly Output Graph: A Graphical Article-Level Metric Indicating the Impact of a Scholar’s Publications. In: Li, J., Li, X., Wang, S., Li, J., Sheng, Q. (eds) Advanced Data Mining and Applications. ADMA 2016. Lecture Notes in Computer Science(), vol 10086. Springer, Cham. https://doi.org/10.1007/978-3-319-49586-6_40

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  • DOI: https://doi.org/10.1007/978-3-319-49586-6_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49585-9

  • Online ISBN: 978-3-319-49586-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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