Ke q, Ahn Y-Y, Sugimoto CR. A systematic identification and analysis of scientists on Twitter. PLoS ONE 2017;12(4):e0175368.
The authors developed a systematic method to discover scientists who are recognized as scientists by other Twitter users and self-identify as scientists through their profile. They studied the demographics, sharing behaviors, and interconnectivity of the identified scientists in terms of discipline and gender. Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists, under-representation of mathematical, physical, and life scientists, and a better representation of women.