Abstract
The ability to handle large amounts of unstructured information, to optimize strategic business opportunities, and to identify fundamental lessons among competitors through benchmarking, are essential skills of every business sector. Currently, there are dozens of social media analytics' applications aiming at providing organizations with informed decision making tools. However, these applications rely on providing quantitative information, rather than qualitative information that is relevant and intelligible for managers. In order to address these aspects, we propose a semi-supervised learning procedure that discovers and compiles information taken from online social media, organizing it in a scheme that can be strategically relevant. We illustrate our procedure using a case study where we collected and analysed the social media discourse of 43 organizations operating on the Higher Public Polytechnic Education Sector. During the analysis we created an "editorial model" that characterizes the posts in the area. We describe in detail the training and the execution of an ensemble of classifying algorithms. In this study we focus on the techniques used to increase the accuracy and stability of the classifiers.

Abstract
Recent advances in mobile device technology have triggered research on using their aggregate computational and/or storage resources to form edge-clouds. Whilst traditionally viewed as simple clients, smart-phones and tablets today have hardware resources that allow more sophisticated software to be installed, and can be used as thick clients or even thin servers. Simultaneously, new standards and protocols, such as Wi-Fi Direct and Wi-Fi TDLS (Tunneled Direct Link Setup), have been established that allow mobile devices to talk directly with each other, as opposed to over the Internet or across Wi-Fi access points. This can, potentially, lead to ubiquitous, low-latency, device-to-device (D2D) communication. In this paper, we study whether D2D protocols can support mobile-edge clouds by benchmarking different protocols and configurations for a specific application. The results show that decentralized device-to-device techniques can be used to efficiently disseminate multimedia contents while diminishing contention in the wireless infrastructure, allowing for up to 65% traffic reduction at the access points.

Abstract
This paper introduces a novel ranking system for competitive sports based around the notion of subgraphs. Although the system is targeted specifically to professional tennis it could be applied to any dominance network due to its generality. The results of about 140,000 tennis matches played between Top-100 players are used to create a colored directed network where colors represent different surfaces and edge direction depends on head-to-read results between players. The main contribution of this work is a ranking system which relies on the occurrences of 4-node directed subgraphs and the positions (or orbits) where the players appear on them. Since the concept of orbit is intrinsically connected with node dominance, appearing frequently in dominant orbits indicates that the player himself is dominant. Even in a very sparse network and without any background knowledge on the tournaments or stages of the matches, our proposal is able to extract meaningful rankings which capture the intricate competitive relationships between players from different eras.

Abstract
This chapter presents the architecture and design of enki, an Integrated Development Environment (IDE) for learning programming languages on massive open online courses (moocs). this environment can be used as a tool by a learning management system (lms) and a typical lms such as moodle can launch it using the learning tool interoperability (lti) api. student authentication tokens are passed via lti, thus integrating enki in the single sign-on domain of the academic institution. the proposed tool has a web user interface similar to those of reference ides, where the learner has access to different integrated tools, from viewing tutorial videos, to solving programming exercises that are automatically evaluated. enki uses several gamification strategies to engage learners, including generic gamifications services provided by odin and the sequencing of educational resources. the course content (videos, pdfs, programming exercises) is progressively disclosed to the learner as he successfully completes exercises. this is similar to what happens in a game, where new levels are unlocked as the previous are completed, thus contributing to the sense of achievement.

Abstract
This paper presents Enki, a web-based IDE that integrates several pedagogical tools designed to engage students in learning programming languages. Enki achieves this goal (1) by sequencing educational resources, either expository or evaluative, (2) by using gamification services to entice students to solve activities, (3) by promoting social interaction and (4) by helping students with activities, providing feedback on submitted solutions. The paper describes Enki, its concept and architecture, details its design and implementation, and covers also its validation.

Abstract
The corner stone of a language development environment is an editor. For programming languages, several code editors are readily available to be integrated in Web applications. However, only few editors exist for diagrammatic languages. Eshu is an extensible diagram editor, embeddable in Web applications that require diagram interaction, such as modeling tools or e-learning environments. Eshu is a JavaScript library with an API that supports its integration with other components, including importing/exporting diagrams in JSON. Eshu was already integrated in a pedagogical environment with automated diagram assessment, configured for extended entityrelationship diagrams, that served as basis for an usability evaluation. © José Paulo Leal, Helder Correia, and José Carlos Paiva;licensed under Creative Commons License CC-BY.