Abstract
For a long time collaborative work has been seen as an important pedagogical methodology. Lately there has been an increased interest in creating tools that allow and foster collaborative work in online and web-based environments. However, despite these efforts most of the available tools today only allow students to participate in a collaborative work. Issues like helping the teacher to create the whole collaborative activity and, helping the students to collaborate with each other are usually left out from the automatic tools. Interestingly, one of the main difficulties that hamper collaboration between students during a course work is that they do not know how to do delegate tasks, how to set deadlines and how to control the colleagues' contribution's in a democratic way. This later issue is particularly important because most collaborative systems do not offer a mechanism to differentiate the group participants in order to assess and grade them individually. In this article we propose and describe a system capable of creating group tasks while providing information that would help to individually assess each group member. The system can be configured in order to leverage the collaboration between students and guiding them in this sort of working methodology. The proposed system features two operating modes: the sequential and the simultaneous activity. It also includes the possibility to establish time limits for each assigned task; an automatic forum for mandatory comments upon referred drawbacks on a colleague's work; a versioning system associated with the simultaneous activity, and the retrieval of all logged interactions, provided in the form of a report which we believe ultimately would help the teacher to differentiate group participants in order to assess their work and grade them individually.

Abstract
The organizational impacts of adopting social media have been on the top key concerns of organizations entering these environments. Organizations are, in fact, allocating time, effort, skills, human resources and technology and this raises the constant need to measure the ROI and legitimize the use of social media in the context of organizational development. However, how can organizations attempt to measure the efficiency and return on investments on a social media content approach that has not been strategically designed? In this paper, we report on previous research which we have further developed into a more comprehensive and solid analysis of types of social media content strategies that are being implemented in the Higher Education Sector, using clustering to group analogue content strategies and social media KPI to measure the efficiency of each of the main i. This work is based on a previously proposed editorial model for the design of social media content strategies for Higher Education Institutions, and results show which are the most relevant strategic areas of communication and corresponding return, in terms of publics' engagement, that organizations can obtain. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
Social networks can often be considered the main stage of news, so detecting newsworthy information in this media is a relevant subject of study. Labeling automatically messages shared in social networks is an area of study that can be used directly to detect newsworthy information or to serve as training data for other projects. The solution presented in this work is to use the news as the base knowledge for the classification of messages. The results of this application were promising, with an accuracy of over 90% in detecting news related messages in our datasets. © 2017 IEEE.

Abstract
The adoption of social media networks by organizations has been increasing, mainly by using more social networks but also by constantly increasing on the number of messages and received comments posted on these channels. Interestingly, this process apparently has not been accompanied by a carefully planned and strategically design process to provide the essential alignment with organizational goals. This study is framed in the tertiary sector, the Higher Education Sector (HES), which despite its peculiarities, is no exception to the above limitations, and is facing an increased competitive environment. In this paper we present a sector benchmarking process, and the respective analysis, to provide insights on the sector's tendency, as well as a threefold classification of the sector's social media strategies being pursued. The analysis builds upon a regulatory communication framework and respective editorial model. We describe the results of our automatic text-mining and categorization information system, specifically developed to address and analyze the seven categories of HES' social media messages. Our results show that social media strategies have been focusing essentially on mediatization and building/maintaining the organizational image/reputation as well as on advertising educational services, but completely neglecting the dialogical dimension intrinsically linked to social media environments. (C) 2015 The Authors. Published by Elsevier B.V.

Abstract
Measuring the return on communication investments on social media has become one of the top key issues for organizations joining social networks. However, this field has been lacking articulation between what is conveyed as social media key performance indicators and the alignment of strategic organizational goals. Therefore, we propose a methodology to measure the performance of each organization on social media, to determine their positioning in the sector and to evaluate which are the content strategies used to boost the highest performing organizations. Thus, we identify how to determine which organizations should be closely monitored within the sector and which type content strategies can foster higher organizational performance on social media. © 2017 Copyright is held by the owner/author(s).

Abstract
Group work is an essential activity during both graduate and undergraduate formation. Although there is a vast theoretical literature and numerous case studies about group work, we haven’t yet seen much development concerning the assessment of individual group participants. The problem relies on the difficulty to have the perception of each student’s contribution towards the whole work. We propose and describe a novel tool to manage and assess individual group. Using the collected interactions from the tool usage we create a model for predicting ill-conditioned interactions which generate alerts. We also describe a functionality to predict the final activity grading, based on the interaction patterns and on an automatic classification of these interactions. © Springer International Publishing Switzerland 2015.