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利用科学社交网络改善PubMed读者的研究策略。

Use of scientific social networking to improve the research strategies of PubMed readers.

作者信息

Evdokimov Pavel, Kudryavtsev Alexey, Ilgisonis Ekaterina, Ponomarenko Elena, Lisitsa Andrey

机构信息

Knowledge Technologies Ltd, Moscow, Russia.

qB Ltd, Moscow, Russia.

出版信息

BMC Res Notes. 2016 Feb 18;9:113. doi: 10.1186/s13104-016-1920-y.

Abstract

BACKGROUND

Keeping up with journal articles on a daily basis is an important activity of scientists engaged in biomedical research. Usually, journal articles and papers in the field of biomedicine are accessed through the Medline/PubMed electronic library. In the process of navigating PubMed, researchers unknowingly generate user-specific reading profiles that can be shared within a social networking environment. This paper examines the structure of the social networking environment generated by PubMed users.

METHODS

A web browser plugin was developed to map [in Medical Subject Headings (MeSH) terms] the reading patterns of individual PubMed users.

RESULTS

We developed a scientific social network based on the personal research profiles of readers of biomedical articles. A browser plugin is used to record the digital object identifier or PubMed ID of web pages. Recorded items are posted on the activity feed and automatically mapped to PubMed abstract. Within the activity feed a user can trace back previously browsed articles and insert comments. By calculating the frequency with which specific MeSH occur, the research interests of PubMed users can be visually represented with a tag cloud. Finally, research profiles can be searched for matches between network users.

CONCLUSIONS

A social networking environment was created using MeSH terms to map articles accessed through the Medline/PubMed online library system. In-network social communication is supported by the recommendation of articles and by matching users with similar scientific interests. The system is available at http://bioknol.org/en/.

摘要

背景

对于从事生物医学研究的科学家而言,每日跟进期刊文章是一项重要活动。通常,生物医学领域的期刊文章和论文是通过Medline/PubMed电子图书馆获取的。在浏览PubMed的过程中,研究人员在不知不觉中生成了特定于用户的阅读档案,这些档案可以在社交网络环境中共享。本文研究了PubMed用户生成的社交网络环境的结构。

方法

开发了一个网络浏览器插件,用于(以医学主题词(MeSH)术语)映射个体PubMed用户的阅读模式。

结果

我们基于生物医学文章读者的个人研究档案开发了一个科学社交网络。一个浏览器插件用于记录网页的数字对象标识符或PubMed ID。记录的条目会发布在活动动态中,并自动映射到PubMed摘要。在活动动态中,用户可以追溯之前浏览过的文章并插入评论。通过计算特定MeSH出现的频率,PubMed用户的研究兴趣可以用标签云直观呈现。最后,可以搜索研究档案以查找网络用户之间的匹配项。

结论

利用MeSH术语创建了一个社交网络环境,以映射通过Medline/PubMed在线图书馆系统访问的文章。文章推荐以及将具有相似科学兴趣的用户进行匹配为网络内的社交交流提供了支持。该系统可在http://bioknol.org/en/获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5ee/4758102/9ea3d58ef56f/13104_2016_1920_Fig1_HTML.jpg

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3
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4
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