During my bachelor's, I picked up Albert-László Barabási's Network Science book for a research project. The premise is elegant: protein interactions, power grids, social media feeds, financial markets, and many other complex systems can be modeled as graphs, with objects as nodes and relationships as edges. Once you have a graph, you can measure things: who is central, what clusters form, how fast information spreads, and whether the network has the "small-world" property where any two nodes are surprisingly close [1].
Scientific collaboration networks fell into this framework naturally and captivated me. I wanted to apply these ideas to Brazilian computer science to answer some questions that I had out of curiosity. The result is a peer-reviewed paper, Beyond Boundaries: Collaboration Networks and Research Output in Brazilian Computer Science, co-authored with André Vignatti, published in the XIV Brazilian Workshop on Social Network Analysis and Mining (BraSNAM) [2]. This post is my attempt to bring the findings out of LaTeX and into plain language, while adding some context about the research.
aliiiimaher•3d ago
Scientific collaboration networks fell into this framework naturally and captivated me. I wanted to apply these ideas to Brazilian computer science to answer some questions that I had out of curiosity. The result is a peer-reviewed paper, Beyond Boundaries: Collaboration Networks and Research Output in Brazilian Computer Science, co-authored with André Vignatti, published in the XIV Brazilian Workshop on Social Network Analysis and Mining (BraSNAM) [2]. This post is my attempt to bring the findings out of LaTeX and into plain language, while adding some context about the research.