D83 - Search; Learning; Information and Knowledge; Communication; Belief; UnawarenessReturn

Debt literacy has been considered to be a critical competence of modern societies since the recent global financial crisis. Debt-literate individuals are less prone to financial abuse and perform better in terms of credit management. Currently, debt-related information and knowledge are widely accessible through social networking sites (SNS), such as Facebook. However, not all SNS users have equal access to debt-related resources, and, consequently, they reach different scores in debt literacy tests. This study examines relational factors (resources) behind the debt literacy of Facebook users (N = 1,055) in Poland by applying the Resource Generator tool built into the online questionnaire. This quantitative instrument helps to diagnose resources that are embedded and mobilised (social capital) from personal networks made up of kin, friends and acquaintances. We found that users with more social capital, that is, better access to resources, perform better in debt literacy tests. Moreover, weak ties (acquaintances) appear to be good sources of debt-related information and knowledge that have positive impact on debt literacy scores.

How is knowledge distributed over space and how are different types of knowledge related? These questions have so far received little attention. In this paper we measure knowledge relatedness based on the relationship between individual patent categories by using coclassification information obtained from EPO patents. We also follow specialization of countries and its evolution over the past three decades. We focus on the EU, the United States and China. The objective of this paper is to identify the knowledge relatedness between technological fields and to map knowledge produced in selected countries. For visualization of knowledge relatedness network analysis has been used.