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Visual analysis of author–keyword relations with eDBLP

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Abstract

In this paper, we describe an approach for visualizing the textual information archived in the DBLP and the static and dynamic relations contained in it. Those relations are existing between authors and co-authors, between keywords, but also between authors and keywords. Visually representing them provides a way to quickly get an overview about emerging or disappearing topics as well as researchers and researcher groups. To reach our goal we apply node-link diagrams, word clouds, heatmaps, and area plots to the preprocessed and transformed DBLP data. Moreover, we use t-SNE as a way to compute groups of authors with similar keywords providing insights about similar research topics. All visualizations are equipped with interaction techniques and are built by using the functionality of the Bokeh library in Python, which enables the users to run the eDBLP in a web browser and to explore the dataset in an interactive and intuitive way. Finally, we discuss limitations and scalability issues of our approach.

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Authors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Michael Burch, Abdullah Saeed, Alina Vorobiova, Armin Memar Zahedani, Linus Hafkemeyer & Marco Palazzo

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  1. Michael Burch
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  2. Abdullah Saeed
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  3. Alina Vorobiova
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  4. Armin Memar Zahedani
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  5. Linus Hafkemeyer
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  6. Marco Palazzo
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Correspondence to Michael Burch.

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Burch, M., Saeed, A., Vorobiova, A. et al. Visual analysis of author–keyword relations with eDBLP. J Vis 25, 897–914 (2022). https://doi.org/10.1007/s12650-021-00817-4

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  • DOI: https://doi.org/10.1007/s12650-021-00817-4

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