Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/124270
Title: Does society show differential attention to researchers based on gender and field?
Authors: González Betancor, Sara María 
Dorta González, Pablo 
UNESCO Clasification: 630909 Posición social de la mujer
Keywords: Investigadoras
Estudios de género
Altmetrics
Social impact
Social media, et al
Issue Date: 2023
Journal: Journal of Informetrics 
Abstract: While not all researchers prioritize social impact, it is undeniably a crucial aspect that adds significance to their work. The objective of this paper is to explore potential gender differences in the social attention paid to researchers and to examine their association with specific fields of study. To achieve this goal, the paper analyzes four dimensions of social influence and examines three measures of social attention to researchers. The dimensions are media influence (mentions in mainstream news), political influence (mentions in public policy reports), social media influence (mentions in Twitter), and educational influence (mentions in Wikipedia). The measures of social attention to researchers are: proportion of publications with social mentions (social attention orientation), mentions per publication (level of social attention), and mentions per mentioned publication (intensity of social attention). By analyzing the rankings of authors -for the four dimensions with the three measures in the 22 research fields of the Web of Science database- and by using Spearman correlation coefficients, we conclude that: 1) significant differences are observed between fields; 2) the dimensions capture different and independent aspects of the social impact. Finally, we use non-parametric means comparison tests to detect gender bias in social attention. We conclude that for most fields and dimensions with enough non-zero altmetrics data, gender differences in social attention are not predominant, but are still present and vary across fields.
URI: http://hdl.handle.net/10553/124270
ISSN: 1751-1577
DOI: 10.1016/j.joi.2023.101452
Source: Journal of Informetrics [1751-1577], v. 17 (4), 101452, noviembre 2023
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