Understanding the Twitter Usage of Science Citation Index (SCI) Journals

被引：1

作者：

Raamkumar, Aravind Sesagiri ^{[1
]}

Erdt, Mojisola ^{[1
]}

Vijayakumar, Harsha ^{[1
]}

Nagarajan, Aarthy ^{[1
]}

Theng, Yin-Leng ^{[1
]}

机构：

[1] Nanyang Technol Univ, Wee Kim Wee Sch Commun & Informat, Singapore 637718, Singapore

来源：

DIGITAL LIBRARIES AT THE CROSSROADS OF DIGITAL INFORMATION FOR THE FUTURE, ICADL 2019 | 2019年 / 11853卷

基金：

新加坡国家研究基金会;

关键词：

Twitter; Journals; Science Citation Index; Social network analysis; Social media; SOCIAL MEDIA PRESENCE;

D O I：

10.1007/978-3-030-34058-2_6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the Twitter interaction patterns of journals from the Science Citation Index (SCI) of Master Journal List (MJL). A total of 953,253 tweets extracted from 857 journal accounts, were analyzed in this study. Findings indicate that SCI journals interacted more with each other but much less with journals from other citation indices. The network structure of the communication graph resembled a tight crowd network, with Nature journals playing a major part. Information sources such as news portals and scientific organizations were mentioned more in tweets, than academic journal Twitter accounts. Journals with high journal impact factors (JIFs) were found to be prominent hubs in the communication graph. Differences were found between the Twitter usage of SCI journals with Humanities and Social Sciences (HSS) journals.

引用

页码：54 / 60

页数：7

共 11 条

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