کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4968135 | 1365185 | 2016 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Posted, visited, exported: Altmetrics in the social tagging system BibSonomy
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users' activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Informetrics - Volume 10, Issue 3, August 2016, Pages 732-749
Journal: Journal of Informetrics - Volume 10, Issue 3, August 2016, Pages 732-749
نویسندگان
Daniel Zoller, Stephan Doerfel, Robert Jäschke, Gerd Stumme, Andreas Hotho,