Andrii Vozniuk
Social media (SM) platforms have demonstrated their ability to facilitate knowledge sharing on the global scale. They are increasingly often employed in educational and humanitarian domains where, despite their general benefits, they expose challenges peculiar to these domains. Specifically, the research context of this thesis is directed by my participation in the Go-Lab European project and my collaboration with Médecins Sans Frontières (MSF) where SM platforms were used extensively. In this thesis, we address four challenges regarding analytics, privacy, discovery, and delivery, aiming to answer corresponding four research questions. How to provide user-oriented analytics in knowledge sharing systems to support awareness and reflection? What privacy management interfaces and mechanisms are suitable for knowledge analytics and learning analytics? How to enable discovery of knowledge relevant to user interests? How to facilitate knowledge delivery into settings where Internet connectivity is limited or absent? Henceforward, we provide an overview of our results. Analytics. To enable awareness and reflection for an SM platform users, we propose the embedded contextual analytics model where the analytics is embedded into the interaction context and presents information relevant to that particular context. Also, we propose two general architectures materializing this model respectfully based on real-time analytical applications and a scalable analytic back-end. Using these architectures, we provided analytics services to the SM platform users. We conducted an evaluation with the users demonstrating that embedded contextual analytics was useful to support their awareness and reflection. Privacy. To address the privacy concerns associated with the recording, storage, and analysis of user interaction traces, we propose a novel agent-based privacy management model. Our proposal uses a metaphor of physical presence of a tracking agent in an interaction context making the platform user aware of the tracking and allows to manage the tracking policy in a way similar to the physical world. We have implemented the proposed privacy interface in an SM platform and obtained positive evaluation results with the users. Discovery. Due to a large number of content items stored in SM platforms, it can be challenging for the users to find relevant knowledge. Addressing this challenge, we propose an interactive recommender system based on user interests enabling discovery of relevant content and people. We have implemented the proposed recommender in an SM platform and conducted two evaluations with platform users. The evaluations demonstrated the ability of the approach to identify relevant user interests and to recommend relevant content. Delivery. At the moment of writing in 2016, near half of the world's population still does not have reliable Internet access. Often, the places where humanitarian action is needed have limited Internet connection. We propose a novel knowledge delivery model that relies on a peer-to-peer middleware and uses low-cost computers for local knowledge replication. We have developed a system implementing the model and evaluated it during eight deployments in MSF missions. The evaluation demonstrated its knowledge delivery abilities and its usefulness for the field staff.
EPFL2017
