/ 2017 - 2018 / Temporal networks in computer science scientometrics
Group project
ROLE: PROGRAMMING SUPPORT
2IMW10 Data Engineering is a course that I followed at Eindhoven University of Technology. The course focused on the main characteristics and relevant research results for models of contemporary data intensive systems, the practical relevance of these models for engineering data intensive applications, the relative advantages and disadvantages of these models and making practical use of contemporary frameworks and technologies implementing these models.

Our chosen project focused on Bibliometrics and Scientometrics, citations analysis to investigate the evolution of science. In order to properly understand the evolution and the structure of scientific research, the analysis of citations alone does not suffice; the focus should thus be on both citations and co-authoring relationships and they should be studied in the form of temporal networks. The focus of this project has been on exploiting the use of temporal graphs tostudy the information diffusion in the Computer Science research field.

The initial large network was built by a group member using Python. This was later loaded into Neo4j and extra relationships were derived using the Cypher graphquery language. We then analyzed the network with a variety of different approaches.