Abstract
Building a researchers affinity network through the automatic processing of their publications allows us to gain a perspective that goes beyond the networks established through co-authorship. The definition of the importance of each researcher is defined upon their bibliographic production volume, i.e., number of publications, and also upon their centrality in the general network of researchers. In fact, the centrality of a researcher in a network reveals its importance in communication flows with other researchers, thus assuming that communication between researchers is itself a relevant factor for organizational life and in its production. Both network and centrality concepts are better interpreted in a graphical way. In this study, we explore the workflow that will provide these visualizations and focus in the empirical selection of the most appropriate centrality measure. We also propose a centrality visualization method that facilitates the interpretation of the selected measures

Abstract
Phonology is a linguistic discipline that is naturally computational. However, as many researchers are not familiar with the use of digital methods, most of the computation required is still performed by humans. This article presents a training experiment of master's students of the phonology seminar at the University of Porto, bringing the research process directly to the classroom. The experiment was designed to raise students' awareness of the potentialities of combining human and machine computation in phonology. The Centre for Digital Culture and Innovation (CODA) readily embraced this project to showcase the application of digital humanities as humanities in both research and training activities. During this experiment, students were trained to collect and process phonological data using various open-source and free web-based resources. By combining a strict protocol with some individual research freedom, the students were able to make valuable contributions towards Creolistic Studies, while enriching their individual skills. Finally, the interdisciplinary nature of the approach has demonstrated its potential within and beyond the humanities and social sciences fields (e.g., linguistics, archaeology, history, geography, ethnology, sociology, and genetics), by also introducing the students to basic concepts and practices of Open Science and FAIR principles, including Linked Open Data.