Information technology is dramatically changing society and work relations nowadays. Different ways of connecting through the Internet and the emergence of social networks have provided the means for individuals to contribute and share personal and professional information affecting the way of accessing the job market. In many cases this is in an unstructured mode, although professional websites often require that information is standardized. The quality of the data offered in professional web portals makes it possible to extract more information than in traditional methods (Zide, Elman, & Shahani-Denning, 2014), and additional aspects can be obtained, such as, for example, social capital (Reiners & Alexander, 2013). Moreover, as using these resources has a low cost (Nikolaou, 2014; Roth, Bobko, Van Iddekinge, & Thatcher, 2016), they are an element of great added value for personnel management in different organizational processes (Madia, 2011), such as recruitment, selection, or hiring. Therefore, companies that do not use social networks in their processes for contacting clients and potential employees are missing a huge opportunity. Specifically, the automated analysis of candidates' profiles to determine the adjustment to a position offers a significant efficiency gain in the process (Faliagka et al., 2014). However, it is true that today most organizations with implemented human resource policies use social networks to a greater or lesser extent. One of the most common uses is electronic recruitment, a form of external recruitment based h t t p s : / / j o u r n a l s. c o p m a d r i d. o rg / j wo p

The use of LinkedIn as a tool in the recruitment and selection process has become routine in human resource management. However, a major drawback of such an approach is the lack of systematic and rigorous inferences on the psychological characteristics of the candidates. Calls have been made by scholars for further research on the psychometric guarantee of LinkedIn as a tool in the selection process. This study adopts signalling theory as a framework for exploring how LinkedIn profile information signals a candidate's soft skills. Using a sample of 169 ITC professionals, through a cross-sectional design, soft skills were measured by means of a self-report questionnaire and LinkedIn profiles were assessed using rubrics for measuring the LinkedIn Big Four. Our findings demonstrate that LinkedIn Big Four Breadth of Professional Experience and Social Capital are valid signals of leadership, communication, problem solving, entrepreneurial and commercial thinking, planning and organization, and teamwork. We discuss the practical and theoretical implications of our results.