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Knowledge communication on social media: a case study of Biomedical Science on Baidu Baike

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Abstract

Social media are considered perfect examples of Web 2.0 applications, which people use to communicate and collaborate together. Baidu Baike, a wiki-like online encyclopedia, is analysed as a typical example in which experts and lay Internet users collaborate. Entries in Biomedical Science section are analysed to reveal communication activities behind the construction of such scholarly entries. The composition of the related entries, references of each entry, cooperation among contributors of entries, and common interests of contributors are analysed with Altmetrics, citation analysis, co-occurrence analysis, and heterogeneous coupling. Altmetrics is used to analyse scholarly communication during the construction of entries. Citation analysis based on references in entries provides a way to establish indirect communication between citing and cited authors, namely the contributors of entries and authors of references. Co-occurrence analysis is used for the analysis of cooperation both among experts and lay Internet users and the distribution of tags of entries. Heterogeneous coupling is used to reveal the relationship among entries based on common references as well as common experts. The results show that literature is referred to during people’s online communication. The citations and tags of entries reflect the interdisciplinary specializations within Biomedical Science. The majority of experts cooperated with someone in the same affiliation but cross-unit cooperation also existed. The common interests of experts indicate that the specialists only master their own field. Moreover, as a typical general public, lay Internet users have a wide range of interests and remain enthusiastic about entry contribution.

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Acknowledgements

The paper is supported by the National Social Science Foundation of China (Grant No. 15CTQ024) and the National Natural Science Foundation of China (Grant No. 71603195, No. 71503091). We have to express appreciation to two anonymous reviewers and editors for their helpful observations and inspiring suggestions. We are also grateful to Professor Hans Hoeken for his comments on a previous version of this article and Joanna Wall from Utrecht University for her great assistance in the language revision. The manuscript was completed when the first author was a visiting scholar at Utrecht University, the Netherlands. The support from Utrecht University is appreciated.

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Cheng, N., Dong, K. Knowledge communication on social media: a case study of Biomedical Science on Baidu Baike. Scientometrics 116, 1749–1770 (2018). https://doi.org/10.1007/s11192-018-2828-1

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