Wenceslao Arroyo Machado is PhD student in Information and Communication Technologies, supported by a FPU predoctoral fellowship at the Department of Information and Communication of the University of Granada (UGR). He holds a degree in Information and Documentation and a master’s degree in Data Science and Computer Engineering (UGR). He has worked as a researcher in the project Knowmetrics - evaluation of knowledge in the digital society funded by the BBVA Foundation and as technical support staff in Medialab UGR. His works focus on scientometrics and other areas derived related to the new paradigm of altmetrics and data science.
Degree in Information and Documentation, 2017
University of Granada
Master's Degree in Data Science and Computer Engineering, 2018
University of Granada
Altmetric project funded by scientific research team grants from the Ministry of Science and Innovation of Spain.
The project combining theoretical propositions with applied developments via the ‘Knowmetrics’ web platform, which constitutes the nucleus of the project and its communication plan.
Altmetric indicators allow exploring and profiling individuals who discuss and share scientific literature in social media. But it is still a challenge to identify and characterize communities based on the research topics in which they are interested as social and geographic proximity also influence interactions. This paper proposes a new method which profiles social media users based on their interest on research topics using altmetric data. Social media users are clustered based on the topics related to the research publications they share in social media. This allows removing linkages which respond to social or personal proximity and identifying disconnected users who may have similar research interests. We test this method for users tweeting publications from the fields of Information Science & Library Science, and Microbiology. We conclude by discussing the potential application of this method and how it can assist information professionals, policy managers and academics to understand and identify the main actors discussing research literature in social media.
This study provides an overview of science from the Wikipedia perspective. A methodology has been established for the analysis of how Wikipedia editors regard science through their references to scientific papers. The method of co-citation has been adapted to this context in order to generate Pathfinder networks (PFNET) that highlight the most relevant scientific journals and categories, and their interactions in order to find out how scientific literature is consumed through this open encyclopaedia. In addition to this, their obsolescence has been studied through Price index. A total of 1 433 457 references available at Altmetric.com have been initially taken into account. After pre-processing and linking them to the data from Elsevier’s CiteScore Metrics the sample was reduced to 847 512 references made by 193 802 Wikipedia articles to 598 746 scientific articles belonging to 14 149 journals indexed in Scopus. As highlighted results we found a significative presence of “Medicine” and “Biochemistry, Genetics and Molecular Biology” papers and that the most important journals are multidisciplinary in nature, suggesting also that high-impact factor journals were more likely to be cited. Furthermore, only 13.44% of Wikipedia citations are to Open Access journals.