Who tweets scientific publications? A large‐scale study of tweeting audiences in all areas of research

Zhang, Lin; Gou, Zhenyu; Fang, Zhichao; Sivertsen, Gunnar; Huang, Ying

doi:10.1002/asi.24830

Cited by 9 publications

(1 citation statement)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, our project's results may provide a basis to build upon for future studies investigating how the media is actually covering the work. Altmetric may also be a flawed metric of impact on the public as previous research has shown that most tweets came from within academia with other academics interacting with them 30 . Notably, the data in our project likely will contain more health research produced from the academic sector as they primarily communicate via articles, books, and chapters, however, we have included pharmaceutical agencies, governmental health bodies, and hospitals (where they have an ROR) which may provide a broader overview of the online coverage of health research in Ireland.…”

Section: Methodsmentioning

confidence: 99%

Altmetric coverage of health research in Ireland 2017-2023: a protocol for a cross-sectional analysis

Sharp,

Logullo,

Murphy

et al. 2024

HRB Open Res

View full text Add to dashboard Cite

Background Scientific publications have been growing exponentially, contributing to an oversaturated information environment. Quantifying a research output’s impact and reach can cannot be solely measured by traditional metrics like citation counts as these have a lag time and are largely focused on an academic audience. There is increasing recognition to consider ‘alternative metrics’ or altmetrics to measure more immediate and broader impacts of research. Better understanding of altmetrics can help researchers better navigate evolving information environments and changing appetites for different types of research. Objectives Our study aims to: 1) analyse the amount and medium of Altmetric coverage of health research produced by Irish organisations (2017 – 2023), identifying changes over time and 2) investigate differences in the amount of coverage between clinical areas (e.g., nutrition vs. neurology) and, where possible, by study types (e.g., clinical trials vs. evidence syntheses). Methods Using Altmetric institutional access, we will gather data on research outputs published 1 January 2017 through 31 December 2023 from active Irish organisations with Research Organisation Registry (ROR) IDs. Outputs will be deduplicated and stratified by their Australian and New Zealand Standard Research Classification relating to ≥1 field of health research: Biological Sciences, Biomedical and Clinical Sciences, Chemical Sciences, Health Sciences, and Psychology. We will clean data using R and perform descriptive analyses, establishing counts and frequencies of coverage by clinical area and medium (e.g., traditional news, X, etc.); data will be plotted on a quarterly and yearly basis. We will use topic modelling using latent Dirichlet allocation to explore prevalent topics over time. Results and Conclusions Improved understanding of one’s information environment can help researchers better navigate their local landscapes and identify pathways for more effective communication to the public. All R code will be made available open-source, allowing researchers to adapt it to evaluate their local landscapes.

show abstract

Section: Methodsmentioning

confidence: 99%

Altmetric coverage of health research in Ireland 2017-2023: a protocol for a cross-sectional analysis

Sharp,

Logullo,

Murphy

et al. 2024

HRB Open Res

View full text Add to dashboard Cite

show abstract

Does disseminating scientific information on social media promote public health during the COVID‐19 pandemic?

Quan,

Zhang

2024

Asso for Info Science & Tech

View full text Add to dashboard Cite

Countries worldwide are transitioning their emergency response activities into long‐term management of COVID‐19. One promising strategy to mitigate the pandemic is combining the widespread use of social media with the potential impact of scientists on science education to create healthier information ecosystems. This study analyzed data from 189 online polls involving 1,391,706 participants who are either Sina Weibo or Tencent WeChat users to explore the impact of scientific information disseminated on social media on public health. This study aimed to address the following questions: (1) Does scientific information disseminated on social media help its audiences avoid becoming infected with COVID‐19? (2) To what extent does scientific information make a difference in the infection rate of its audiences? Our study found that the COVID‐19 un‐infection rate of the audiences receiving scientific information is significantly higher than that of the general social media users. There is a significant and lasting positive correlation between the dissemination of scientific information and the un‐infection rate of its audiences. We suggest that creating healthier information ecosystems should be integrated into the long‐term management of COVID‐19, as updating the public's beliefs about the pandemic is fundamental to mitigating the ongoing threat of the COVID‐19 pandemic.

show abstract

How fast do scholarly papers get read by various user groups? A longitudinal and cross‐disciplinary analysis of the evolution of Mendeley readership

Fang,

Ho,

Han

et al. 2024

Asso for Info Science & Tech

View full text Add to dashboard Cite

To provide a dynamic perspective on the evolution of Mendeley readership, this study conducts an 8‐year longitudinal analysis of approximately 3.4 million scholarly papers published in 2015. Mendeley readership data were collected annually from 2016 to 2023 for the sampled papers to analyze the temporal accumulation patterns of readership following publication. The results indicate that Mendeley readership exhibits a speed advantage compared to citations and a prevalence advantage compared to Twitter mentions, demonstrating both initial prevalence and sustained growth on a yearly basis. However, the patterns of accumulation vary across disciplines, with papers in Biomedical and Health Sciences showing the fastest accrual of extensive Mendeley readership data. Leveraging demographic data provided by Mendeley, this study further investigates how different user groups—categorized by academic status, disciplinary affiliation, and geographic location—engage with papers across various disciplines. The findings highlight Mendeley readership as a rapid and substantial altmetric, yet they also emphasize the need to interpret the nature of the attention captured by Mendeley readership with caution, considering its potential biases introduced by the varying engagement levels of different user groups across disciplines.

show abstract

Who tweets scientific publications? A large‐scale study of tweeting audiences in all areas of research

Cited by 9 publications

References 43 publications

Altmetric coverage of health research in Ireland 2017-2023: a protocol for a cross-sectional analysis

Altmetric coverage of health research in Ireland 2017-2023: a protocol for a cross-sectional analysis

Does disseminating scientific information on social media promote public health during the COVID‐19 pandemic?

How fast do scholarly papers get read by various user groups? A longitudinal and cross‐disciplinary analysis of the evolution of Mendeley readership

Contact Info

Product

Resources

About