Online misbehaviour means we cannot take the information received via social media at face value: sharing of misleading or simply false information and coordinated behaviour distorts the quality of information. Additionally, by design, each user is exposed to a unique view of the information landscape. Every user should be able to answer the questions: “How am I being misinformed?” and “How does my unique position shape the information I receive?” Leveraging a multilayer network approach to detect misbehaviour and describe users' positions in the dynamic information space, the CON-NET project aims to enable users to answer these questions. CON-NET will develop machine learning techniques to identify trends, signals, and suspicious behaviours as well as misbehaving entities. We will create an online platform visualising these multilayer networks, which will allow an end user to better understand the source and impact of online misbehaviour.

2023

2025