Information technology and top management support are considered infrastructure for knowledge sharing. This research aims to identify infrastructure profiles and their relationship with knowledge... Show More

Information technology and top management support are considered infrastructure for knowledge sharing. This research aims to identify infrastructure profiles and their relationship with knowledge sharing. A survey method was adopted involving 231 respondents working in information technology teams in Brazil. The analysis identified four profiles, namely: focus on information technology; focus on top management support; adrift; and knowledge sharing oriented. The latter was identified as being the most effective, while no significant difference was found between the other clusters in relation to knowledge sharing. This finding is a supplement to this field of knowledge because, in addition to confirming the relevance of the two constructs, it shows that their simultaneous presence contributes to knowledge sharing. This result also helps managers by highlighting that in order to leverage knowledge sharing it is necessary to signal the importance of the process for the company, as well as provide adequate information technology.

Social networks have become popular and are now becoming an alternate mean of communication, used to share information on various topics, ranging from politics or sports to simple aspects of... Show More

Social networks have become popular and are now becoming an alternate mean of communication, used to share information on various topics, ranging from politics or sports to simple aspects of everyday life. Twitter messages (tweets) are shared in real time and are essentially public, making them a useful source of information for areas such as tourism, marketing, health, and safety. This paper describes an information system that involves the creation and storage of a corpus of tweets, written in European Portuguese and published within the Portuguese territory. The system also involves a REST API that allows access to the stored information, and a web-based dashboard that makes it possible to analyze and visualize indicators concerning the stored data.

With the emergence of Virtual Learning Environments (VLE) in the educational context, the teaching forms are undergoing transformations, both for distance and presential learning. The growing use of... Show More

With the emergence of Virtual Learning Environments (VLE) in the educational context, the teaching forms are undergoing transformations, both for distance and presential learning. The growing use of VLE and the acceptance of this technology, its behavior and its success is directly related to its adoption by teachers and students. The technology adoption has been studied in recent decades, and many analysis models have been proposed. This study is based on the Unified Theory of Acceptance and Use of Technology model, that is an attempt at an assembly of constructs from other theories and models. However, this model still has not addressed gaps and not discussed issues when applied to some contexts. This article aims to propose an extension of UTAUT model for analysis of VLE adoption as support to presential learning, including new elements such as interactivity, monitoring and continuity of use.

The evolution of technology, along with the common use of different devices connected to the Internet, provides a vast growth in the volume and variety of data that are daily generated at high... Show More

The evolution of technology, along with the common use of different devices connected to the Internet, provides a vast growth in the volume and variety of data that are daily generated at high velocity, phenomenon commonly denominated as Big Data. Related with this, several Text Mining techniques make possible the extraction of useful insights from that data, benefiting the decision-making process across multiple areas, using the information, models, patterns or tendencies that these techniques are able to identify. With Sentiment Analysis, it is possible to understand which sentiments and opinions are implicit in this data. This paper proposes an architecture for Sentiment Analysis that uses data from the Twitter, which is able to collect, store, process and analyse data on a real-time fashion. To demonstrate its utility, practical applications are developed using real world examples where Sentiment Analysis brings benefits when applied. With the presented demonstration case, it is possible to verify the role of each used technology and the techniques adopted for Sentiment Analysis.