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Computer games are currently one of the computer science applications with the highest amount of users. "Serious gaming" approaches try to use the attraction of playing games to convey serious content in an entertaining way. This paper presents a multi-agent-architecture for collaborative, serious and casual games. We are combining serious games with casual games, as these are known to have a high potential for frequent gaming by people of various social and educational background. To be flexible concerning the learning domain an ontology-based approach has been used. Thus, new games for different knowledge domains can be created by exchanging the ontology accordingly. Furthermore, we use a "game with a purpose" approach to enable the computer to learn new facts about the games knowledge domain to ease the effort of adapting the basic game to the intended target domain. The presented system is capable of proposing candidates for missing relations in the underlying ontology as well as pointing out possible misconceptions - either within the ontology or by the players - using various heuristics including "wisdom of the crowds" methodologies. The feasibility of the presented approach and its implementation (the Matchballs game) is shown by three case studies each focusing on one aspect of the system. [ABSTRACT FROM AUTHOR]

Although much has been published regarding street protests on social media, few works have attempted to characterize social media users' spatial behavior in such events. The research reported here uses spatial capture-recapture methods to determine the influence of the built environment, physical proximity to protest location, and collective posting rhythm on variations in users' spatial detectability and density during a protest in Mexico City. The best-obtained model, together with explaining the spatial density of users, shows that there is high variability in the probability of detection of social media user protest supporters and that the collective posting rhythm and the day of observation are significant explanatory factors. The implication is that studies of collective spatial behavior would benefit by focussing on users' activity centres and their urban environment, rather than their physical proximity to the protest location, the latter being unable to adequately explain spatial variations in users' probability of detection and density during the protest event. [ABSTRACT FROM AUTHOR]