[Purpose/significance] Online academic social networking provides an effective way and novel views to quickly monitor the trend of science development and deeply understand scientific implication. [Method/process] An analytic framework was proposed to find the pattern of academic social networking in China by tracing the relations among all pairs of disciplines, with the comparisons in the two dimensions of impacts and trans-disciplines respectively. Furthermore, empirical research was conducted by using samples from the platform Science Net, in views of three levels of disciplines categories respectively, i.e. field of disciplines, first-level disciplines, second-level disciplines, in which friend relationship was concerned. [Result/conclusion] Firstly, it was found that field of life sciences shows an advantage in size of users registered in the online platform, while field of comprehensive management presents an advantage of tendency to carry out academic social networking, with method of descriptive statistics. Secondly, in term of method combining statistics analysis and Sankey diagram, it was found that a group of relevant disciplines belonging to the first level disciplines, with computer sciences as their core position, have become hot disciplines in social networking, such as automation, electronics and information system, management science and engineering, library information and philology. Lastly but not least, based on the two-dimensional quadrant diagram, conclusions came out that discipline pattern of academic social networking show the characteristics of diversity and dynamics during the switching among three levels of disciplines, and only a few patterns can be stable all the time. For examples, field of comprehensive management exceedingly tend to be trans-disciplines in academic social networking, high impacts would turn out in the field of life sciences, but low impacts in the first level discipline of computer science.
Duan Qingfeng
,
Feng Zhen
. Empirical Research on the Pattern of Online Academic Social Networking in Views of Multilevel Discipline Categories in China: A Case of Science Net[J]. Library and Information Service, 2019
, 63(6)
: 85
-96
.
DOI: 10.13266/j.issn.0252-3116.2019.06.011
[1] 韩文, 刘畅, 雷秋雨. 分析学术社交网络对科研活动的辅助作用——以researchgate和academia.Edu为例[J]. 情报理论与实践, 2017, 40(8):105-111.
[2] 周庆山, 杨志维. 学术社交网络用户行为研究进展[J]. 图书情报工作, 2017, 61(16):38-47.
[3] 张耀坤, 张维嘉, 胡方丹. 中国高影响力学者对学术社交网站的使用行为调查——以教育部长江学者为例[J]. 情报资料工作, 2017(3):96-101.
[4] 赵杨, 李露琪. 国内外学术社交网络研究现状述评与思考[J]. 情报资料工作, 2016(6):41-47.
[5] 刘春丽, 何钦成. 不同类型选择性计量指标评价论文相关性研究——基于mendeley、f1000和googlescholar三种学术社交网络工具[J]. 情报学报, 2013, 32(2):206-212.
[6] OH J S, WEI J. Groups in academic social networking services——an exploration of their potential as a platform for multi-disciplinary collaboration[C]//IEEE third international conference on privacy, security, risk and trust. Boston:IEEE, 2011:545-548.
[7] JIANG J, NI C, HE D, et al. Mendeley group as a new source of interdisciplinarity study:how do disciplines interact on mendeley?[C]//Proceedings of the 13th ACM/IEEE-CS joint conference on digital libraries. Indianapolis:ACM, 2013:135-138.
[8] JENG W, HE D, JIANG J. User participation in an academic social networking service:a survey of open group users on Mendeley[J]. Journal of the American Society for Information Science and Technology, 2015, 66(5):890-904.
[9] MOHAMMADI E, THELWALL M. Mendeley readership altmetrics for the social sciences and humanities:research evaluation and knowledge flows[J]. Journal of the American Society for Information Science and Technology, 2014, 65(8):1627-1638.
[10] THELWALL M, KOUSHA K. Researchgate articles:age, discipline, audience size, and impact[J]. Journal of the Association for Information Science & Technology, 2017, 68(2):468-479.
[11] 耿斌, 孙建军. 在线学术社交平台的用户行为研究——以researchgate平台南京大学用户为例[J]. 图书与情报, 2017(5):47-53.
[12] 邓胜利, 向阳. 基于学术社交网络的文献阅读及学科关注点差异研究[J]. 图书情报工作, 2017, 61(6):99-106.
[13] 侯治平, 黄少杰, 李昕宸, 等. 学术事件社交网络结构及信息传播规律研究——以科学网屠呦呦获诺贝尔奖博文为例[J]. 情报资料工作, 2017(5):34-41.
[14] 邹儒楠, 于建荣. 数字时代非正式学术交流特点的社会网络分析——以小木虫生命科学论坛为例[J]. 情报科学, 2015(7):81-86.
[15] 段庆锋. 我国科研人员在线学术社交模式实证研究:以科学网为例[J]. 情报杂志, 2015(9):97-101.
[16] THELWALL M, KOUSHA K. Academia.Edu:Social network or academic network?[J]. Journal of the Association for Information Science & Technology, 2014, 65(4):721-731.
[17] VAN N R. Online collaboration:scientists and the social network[J]. Nature, 2014, 512(7513):126-9.
[18] 黄颖, 高天舒, 王志楠, 等. 基于Web of Science分类的跨学科测度研究[J]. 科研管理, 2016, 37(3):124-132.
[19] PORTER A L, COHEN A S, ROESSNER J D, et al. Measuring researcher interdisciplinarity[J]. Scientometrics, 2007, 72(1):117-147.
[20] 段庆锋, 潘小换. 利用社交媒体识别学科新兴主题研究[J]. 情报学报, 2017, 36(12):1216-1223.
[21] 段庆锋, 朱东华. 基于合著与引文混合网络的协同评价方法研究[J]. 情报学报, 2012, 31(2):189-195.
[22] 张帅, 李晶, 王文韬. 学术社交网站用户社交不足的影响机理:基于质性方法的探索[J]. 图书情报工作, 2018, 62(4):81-88.
