论文标题

Twitter指标的稳定性:关于不可用的Twitter的研究提到了科学出版物

The stability of Twitter metrics: A study on unavailable Twitter mentions of scientific publications

论文作者

Fang, Zhichao, Dudek, Jonathan, Costas, Rodrigo

论文摘要

本文调查了随着时间的流逝,Twitter科学出版物的稳定性。 For this, we conducted an analysis of the availability statuses of over 2.6 million Twitter mentions received by the 1,154 most tweeted scientific publications recorded by Altmetric.com up to October 2017. Results show that of the Twitter mentions for these highly tweeted publications, about 14.3% have become unavailable by April 2019. Deletion of tweets by users is the main reason for unavailability, followed by suspension and protection of Twitter user accounts.这项研究提出了两种描述出版物的Twitter传播结构的措施:独创性程度(即,纸张收到的原始推文的比例)和集中程度(即,转发集中在单个原始推文上的程度)。由于其Twitter提到的潜在消失,观察到具有相对较低原创性和相对较高专注力的出版物的Twitter指标,其风险更大。鉴于这些结果,我们强调了关注不稳定Twitter计数的潜在风险的重要性,以及在研究科学出版物的Twitter指标时识别不同Twitter传播结构的重要性。

This paper investigates the stability of Twitter counts of scientific publications over time. For this, we conducted an analysis of the availability statuses of over 2.6 million Twitter mentions received by the 1,154 most tweeted scientific publications recorded by Altmetric.com up to October 2017. Results show that of the Twitter mentions for these highly tweeted publications, about 14.3% have become unavailable by April 2019. Deletion of tweets by users is the main reason for unavailability, followed by suspension and protection of Twitter user accounts. This study proposes two measures for describing the Twitter dissemination structures of publications: Degree of Originality (i.e., the proportion of original tweets received by a paper) and Degree of Concentration (i.e., the degree to which retweets concentrate on a single original tweet). Twitter metrics of publications with relatively low Degree of Originality and relatively high Degree of Concentration are observed to be at greater risk of becoming unstable due to the potential disappearance of their Twitter mentions. In light of these results, we emphasize the importance of paying attention to the potential risk of unstable Twitter counts, and the significance of identifying the different Twitter dissemination structures when studying the Twitter metrics of scientific publications.

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