Abstract
In this paper, we begin to address the question of which scientists are online. Prior studies have shown that Web users are only a segmented reflection of the actual off-line population, and thus when studying online behaviors we need to be explicit about the representativeness of the sample under study to accurately relate trends to populations. When studying social phenomena on the Web, the identification of individuals is essential to be able to generalize about specific segments of a population off-line. Specifically, we present a method for assessing the online activity of a known set of actors. The method is tailored to the domain of science. We apply the method to a population of Dutch computer scientists and their coauthors. The results when combined with metadata of the set provide insights into the representativeness of the sample of interest.
The study results show that scientists of above-average tenure and performance are overrepresented online, suggesting that when studying online behaviors of scientists we are commenting specifically on the behaviors of above-average-performing scientists. Given this finding, metrics of Web behaviors of science may provide a key tool for measuring knowledge production and innovation at a faster rate than traditional delayed bibliometric studies.
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Birkholz, J.M., Wang, S., Groth, P., Magliacane, S. (2013). Who Are We Talking About? Identifying Scientific Populations Online. In: Li, J., Qi, G., Zhao, D., Nejdl, W., Zheng, HT. (eds) Semantic Web and Web Science. Springer Proceedings in Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6880-6_21
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DOI: https://doi.org/10.1007/978-1-4614-6880-6_21
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