Skip Nav Destination
Close Modal
Update search
NARROW
Format
Journal
Date
Availability
1-2 of 2
Rodrigo Costas
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Journal Articles
Publisher: Journals Gateway
Quantitative Science Studies (2021) 2 (3): 1023–1047.
Published: 05 November 2021
FIGURES
| View All (9)
Abstract
View article
PDF
This study investigates the scientific mobility and international collaboration networks in the Middle East and North Africa (MENA) region between 2008 and 2017. By using affiliation metadata available in scientific publications, we analyze international scientific mobility flows and collaboration linkages. Three complementary approaches allow us to obtain a detailed characterization of scientific mobility. First, we uncover the main destinations and origins of mobile scholars for each country. Results reveal geographical, cultural and historical proximities. Cooperation programs also contribute to explain some of the observed flows. Second, we use the academic age. The average academic age of migrant scholars in MENA was about 12.4 years. The academic age group 6–10 years is the most common for both emigrant and immigrant scholars. Immigrants are relatively younger than emigrants, except for Iran, Palestine, Lebanon, and Turkey. Scholars who migrated to Gulf Cooperation Council countries, Jordan, and Morocco were on average younger than emigrants by 1.5 years from the same countries. Third, we analyze gender differences. We observe a clear gender gap: Male scholars represent the largest group of migrants in MENA. We conclude by discussing the policy relevance of the scientific mobility and collaboration aspects.
Includes: Supplementary data
Journal Articles
Publisher: Journals Gateway
Quantitative Science Studies (2020) 1 (2): 771–791.
Published: 01 June 2020
FIGURES
| View All (7)
Abstract
View article
PDF
This paper presents a new method for identifying scholars who have a Twitter account from bibliometric data from Web of Science (WoS) and Twitter data from Altmetric.com . The method reliably identifies matches between Twitter accounts and scholarly authors. It consists of a matching of elements such as author names, usernames, handles, and URLs, followed by a rule-based scoring system that weights the common occurrence of these elements related to the activities of Twitter users and scholars. The method proceeds by matching the Twitter accounts against a database of millions of disambiguated bibliographic profiles from WoS. This paper describes the implementation and validation of the matching method, and performs verification through precision-recall analysis. We also explore the geographical, disciplinary, and demographic variations in the distribution of scholars matched to a Twitter account. This approach represents a step forward in the development of more advanced forms of social media studies of science by opening up an important door for studying the interactions between science and social media in general, and for studying the activities of scholars on Twitter in particular.