The data collected in social media platforms has become an important source of information, usually exploited by a social recommender system to generate suggestions inside the platform. However, social interactions take many forms that go beyond what happens inside social media platforms, both online (e.g., chats) and offline (group activities performed together), and include “indirect’” forms of interacthtions, such as editing and reading collaborative resources. The aim of this workshop is to collect ideas on social interaction-based recommender systems, i.e., systems that in their processing consider the social interactions of the users in novel ways. The idea is to extend the classic notion of social recommendation, by using social interaction data to both produce suggestions inside the social media domain (e.g., recommending persons or social media contents, as in social recommenders) and to improve the existing recommendation technologies in other contexts (e.g., online news, online shopping, healthcare, etc.). The workshop will cover both the industrial and academic aspects of this research area, with keynote speakers and research papers from both sides, ending with a discussion that will try both to highlight the gap that still exists between the two and to create new collaborations. More info at workshop website