Abstract— The low share of women in computer science is documented by many surveys. Most of these studies are based on registrations or enrolments of universities or other scientific institutions. In this paper, we present a new approach to a) analyse the gender gap in the group of scientists that are currently active in research and b) classify differences for different fields of computer science. This group comprises professors, industrial researchers, senior lecturers, postdoctoral researchers, and doctoral students shortly before finishing their theses. The proportion of women in a specific scientific area of computer science might provide valuable information for strategies to recruit women as postdocs or professors.
Science-Metrix develops bibliometric indicators to measure women’s contribution to Science, based on NamSor Gender API.
Using a library or an APIs to infer the gender from a given name, is a common way to fix
A new research by Elsevier used NamSor Gender API along with other methods, to provide an analysis of research performance through
A new paper published in the Global Journal of Enterprise Information System explores how social media analysis can be applied to
Yvonne Mburu is a scientist from Kenya and founder of Med in Africa. She wants to create a global network of African scientists and health professionals to tackle the cultural biases that affect the visibility of African science.
LinkedIn has become the largest professional network, globally. It is a rich source of data for social researchers working on
Top 20 baby names of Ivory Coast (Côte d’Ivoire). We’re working hard to make NamSor the best API to process African names, both for Gender studies as well as Diaspora studies.
35% of ~581 speakers at VivaTech 2017 were women. Now, anyone can help dis-aggregate gender data, simply by inferring gender accurately from personal names.