Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/128198
Título: Factors that Influence How Scientific Articles and Reviews are Mentioned on Twitter
Autores/as: Dorta González, Pablo 
Clasificación UNESCO: 570106 Documentación
630203 Diseño de investigación social
Palabras clave: Altmetrics
News
Public Policy
Social Media
Twitter
Fecha de publicación: 2023
Publicación seriada: Journal Of Scientometric Research 
Resumen: Governments are increasingly pushing researchers to engage in activities with societal impact, emphasizing the need for research dissemination and engagement with the broader public. This study addresses this imperative by investigating the multifaceted factors that influence social media attention, particularly on Twitter, for scientific research. Using Altmetric data and employing multiple linear regression analysis, this paper explores the determinants of Twitter mentions for research outputs. The study shows that certain factors have a significant impact on the level of engagement. In particular, the presence of research in mainstream news emerges as the most influential factor, highlighting the power of media coverage in increasing research visibility. In addition, research topics that align with highly topical issues, such as the COVID-19 pandemic, also garner significant attention on Twitter. Conversely, the influence of expert recommendations and the consolidation of knowledge in the form of review articles have a relatively weaker impact on Twitter mentions. In addition, this study underscores that public policy references in reports and citations within Wikipedia have limited influence in driving social media attention. Interestingly, mentions in patent applications do not have a significant impact in this context. In conclusion, this study provides valuable insights into the dynamics of research dissemination in the digital age and sheds light on the nuanced factors that can enhance or diminish its societal impact on Twitter.
URI: http://hdl.handle.net/10553/127856
http://hdl.handle.net/10553/128198
ISSN: 2321-6654
DOI: 10.5530/jscires.12.3.055
Fuente: Journal of Scientometric Research [ISSN 2321-6654], v. 12 (3), p. 577-584, (Septiembre 2023)
Colección:Artículos
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