Mining People Analytics from StackOverflow Job Advertisements

Abstract

Skills and competences of people participating in online professional networks constitute an ever-increasing new source for data collection and analysis. An important sub-domain of human resources management (HRM) is the recruitment process. Job advertisements and people profiles are main parts of recruitment and since are now available online, they constitute a key factor of a new e-recruitment era. Data mining for erecruitment analysis is important in order to extract a knowledge base for people analytics. Skills and competences are the key variables for people analytics and can be drawn from job advertisements. Leveraging the raw information of online job offers, provides a rich source for people analytics. Detecting the appropriate skills and competences for a job from raw text data and associate them with a job seeker is an increasing challenge. The main objective of this paper is the proposal of a framework aiming to collect online job advertisements from a web source which concerns IT job offers and to extract from the raw text the required skills and competences for specific jobs. The selected professional networking web source is StackOverflow and multivariate statistical data analysis was used to test the correlations between skills and competences in the job offers dataset. The present work falls in a relatively new field of research, concerning the competence mining of peopleware data with special focus on software development.