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Structure and pattern of social tags for keyword selection behaviors

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Abstract

This article identifies patterns and structures in the social tagging of scholarly articles in CiteULike. Using a dataset of 4,215 tags attributed to 1,600 scholarly articles from 15 library and information science journals, a network was built to understand users’ information organization behavior. Social network analysis and the frequent-pattern tree method were used to discover the implicit patterns and structures embedded in social tags as well as in their use, based on 26 proposed tag categories. The pattern and structure of this network of social tags is characterized by power-law distribution, centrality, co-used tag categories, role sharing among tag categories, and similar roles of tag categories in associating distinct tag categories. Furthermore, researchers generated 21 path-based decision-making sub-trees providing valuable insights into user tagging behavior for information organization professionals. The limitations of this study and future research directions are discussed.

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Acknowledgments

We are grateful for the helpful comments of the reviewers. The work described in this paper was partially supported by the Taiwan E-learning and Digital Archives Program (TELDAP) sponsored by the National Science Council of Taiwan under NSC Grants: NSC 101-2631-H-001-005, 101-2631-H-001-006, & 101-2631-H-001-014.

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Authors and Affiliations

  1. Graduate Institute of Library and Information Studies, National Taiwan Normal University, Taipei, Taiwan

    Hao-Ren Ke & Ya-Ning Chen

  2. Computing Center, Academia Sinica, Taipei, Taiwan

    Ya-Ning Chen

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  1. Hao-Ren Ke
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  2. Ya-Ning Chen
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Correspondence to Ya-Ning Chen.

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Ke, HR., Chen, YN. Structure and pattern of social tags for keyword selection behaviors. Scientometrics 92, 43–62 (2012). https://doi.org/10.1007/s11192-012-0718-5

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