Datasets for DEXA 2015 PaperAnalyzing the Strength of Co-authorship Ties with Neighborhood OverlapMichele A. Brandão, Mirella M. MoroDepartamento de Ciência da Computação Universidade Federal de Minas Gerais, Belo Horizonte, MG {micheleabrandao,mirella}@dcc.ufmg.br AbstractEvaluating researchers' scientific productivity usually relies on bibliometry only, which may not be always fair. Here, we take a step forward on analyzing such data by exploring the strength of coauthorship ties in social networks. Specifically, we build co-authorship social networks by extracting the datasets of three research areas (sociology, medicine and computer science) from a real digital library and analyze how topological properties relate to the strength of ties. Our results show that different topological properties explain variations in the strength of co-authorship ties, depending on the research area. Also, we show that neighborhood overlap can be applied to scientific productivity evaluation and analysis beyond bibliometry. DatasetsLinks to the complete datasets used in the experiments: |