Scientific studies are usually developed by contributions from different researchers. Analyzing such collaborations is often necessary, for example, when evaluating the quality of a research group. Also, identifying new partnership possibilities within a set of researchers is frequently desired, for example, when looking for partners in foreign countries. Both analysis and identification are not easy tasks, and are usually done manually. This work presents VRRC, a new approach for visualizing recommendations of people within a co-authorship network (i.e., a graph in which nodes represent researchers and edges represent their co-authorships). VRRC input is a publication list from which it extracts the co-authorships. VRRC then recommends which relations could be created or intensified based on metrics designed for evaluating co-authorship networks. Finally, VRRC provides brand new ways to visualize not only the final recommendations but also the intermediate interactions within the network, including: a complete representation of the co-authorship network; an overview of the collaborations evolution over time; and the recommendations for each researcher to initiate or intensify cooperation. Some visualizations are interactive, allowing to filter data by time frame and highlighting specific collaborations. The contributions of our work, compared to the state-of-art, can be summarized as follows: (i) VRRC can be applied to any co-authorship network, it provides both net and recommendation visualizations, it is a Web-based tool and it allows easy sharing of the created visualizations (existing tools do not offer all these features together); (ii) VRRC establishes graphical representations to ease the visualization of its results (traditional approaches present the recommendation results through simple lists or charts); and (iii) with VRRC, the user can identify not only new possible collaborations but also existing cooperation that can be intensified (current recommendation approaches only indicate new collaborations). This work was partially supported by CNPq, Brazil.