Aims and Scope

Context. The wide adoption of social networks resulted in an ocean of data which presents an interesting opportunity for performing data mining and knowledge discovery in a real-world context. The enormity and high variance of the information that propagates through large user communities influences the public discourse in society and sets trends and agendas in topics that range from marketing, education, business and medicine to politics, technology and the entertainment industry. Mining the contents of social networks provides an opportunity to discover social structure characteristics, analyze action patterns qualitatively and quantitatively, and gives the ability to predict future events. The recent highly impressive advances in deep learning and natural language processing present exciting opportunities for developing automatic methods for the collection, extraction, representation, analysis, and validation of social media data for real-world applications. In recent years, decision makers have become savvy about how to translate social data into actionable information in order to leverage them for a competitive advantage. 

Goal. Traditional research in social network mining mainly focuses on descriptive methods such as community detection, finding central users, behavioural analysis and anomaly (misbehaviour) detection. The main distinguishing focus of this workshop will be the use of social network data for building predictive models that can be used to uncover hidden and unexpected aspects of user-generated content.  The goal is to to extract actionable insights from the data, and to transform the resulting insights into effective actions. In business applications related to for example viral marketing, this could help improve a corporate strategy. In applications in socio-economics, novel insights may shed new light on social theories related to for example social influence or social capital. Regardless of whether it is business or science, the aim is to obtain real-world insights. Thus, the workshop's main focus is on social network analysis and mining techniques to gain actionable real-world insights.