December 2020

Abstract: Given a node-attributed network of Twitter users, can we capture their posting behavior over time and identify patterns that could probably describe, model or predict their activity? Based on the assumption that such posts are topic-specific, can we identify temporal connectivity patterns that emerge from the use of specific attributes? More challengingly, are there […]

Abstract: Aggression in online social networks has been studied mostly from the perspective of machine learning which detects such behavior in a static context. However, the way aggression diffuses in the network has received little attention as it embeds modeling challenges. In fact, modeling how aggression propagates from one user to another, is an important

Abstract: Activity of users in Online Social Networks (OSN) leaves traces that reflect their personality characteristics. The study of these traces is important for a number of fields, such as a social science, psychology, OSN, marketing, and others. Despite a marked increase on research in personality prediction on the basis of online behavior the focus

Abstract: In today’s connected society, many people rely on mHealth and self-tracking (ST) technology to help them break their sedentary lifestyle and stay fit. However, there is scarce evidence of such technological interventions’ effectiveness, and there is no standardized method to evaluate their short- and long-term impact on people’s physical activity and health. This work