Partnerships Analysis Based on Measurements of Common Research Interest

Governments and organizations have been promoting “effective public, public-private and civil society partnerships, building on the experience and resourcing strategies of partnerships”, following the commitment of the United Nations in the Sustainable Development Goals (SDGs) guidelines for environmental conservation. Finding collaborators can also help the group managers understanding the collaboration patterns in various teamwork tasks. We believe that analysis on related data sets can benefit the process toward these goals. In this work, a methodology is designed for discovering research partnerships using researchers’ profiling data from university’s academic data sets. Departing from the conventional partnerships model of researching author-related or reference-related information. We have developed an innovative model that focuses on connecting two related researchers within specific groups and across various fields of study. The fields are defined by researcher’s self-defined region, publication keywords, plan keywords…etc. We explored the relationships using the commonly employed statistical method in evidence-based medicine, odds ratio analysis. In the end, our research yielded novel expertise-based social networks that assist researchers in identifying potential collaborators.