, Ronaldo Correia, Rogério Eduardo Garcia, Danilo Eler, Celso Olivete
Universidade Estadual Paulista. São Paulo Brazil
The content posted on the online social networks has some interesting features, such as, the wide data availability, the range of subject and constant updates, however its important to know how to use these data to generate knowledge. This paper presents a tool that use data mining technics to explore job posts published on LinkedIn, the goal is to define the professional profile described in these job posts. The keyword extraction and the generation of association rules was employed to do that. The results allows a researcher to identify the most relevant skills and the relations between them.