A Wikipédia como fonte de informação de referência: avaliação e perspectivas

Wikipedia is cited in high-profile scientific journals, despite its poor reputation as information source. What warrants this acceptance by scientists? In search for answers, this article presents an assessment of the English Wikipedia according to Silberger's guide for reference works, analyzing its purpose, scope, arrangement, information given, access, and special characteristics, with an additional aspect: quality control of new content. An account of the author's experience in creating an entry in the Portuguese Wikipedia complements the assessment. In conclusion, Wikipedia has high quality content, with advantages such as the large volume of content in many languages, as well as disadvantages such as the emphasis on “popular” topics. There is also inadequate content, whose containment and repair depend on the literacy and engagement of the linguistic community that publishes it, as well as on following Wikipedia's editorial principles. Content creation is an opportunity to engage higher education students, as well as content evaluation, which is a form of peer review. Fruitful use of Wikipedia content depends essentially on the reader's critical judgment

Inovações na revisão por pares: o papel do software

An international group of 33 scientists, led by Tennant, recently released their multidisciplinary perspective on future and emerging innovations for editorial peer review inspired in Web 2.0 platforms: Amazon, Blockchain, GitHub, Hypothesis, Reddit, Stack Exchange, and Wikipedia. Several innovations proposed are actions to be carried out by artificial agents, in line with Fuchs' concept of sociotechnological system, in which the properties emerge from human-machine dynamic collaboration. The research objective was to identify knowledge-intensive automatable tasks among the innovations described. What are these processes performed by software and what other actors in the system do they involve? The research objective was to identify these processes and actors involved. This is a bibliographic research using as corpus the study of emerging innovations by Tennant et al. Of 56 identified passages that refer to automatable peer review functions and tasks, 44 were discarded for focusing on bureaucratic activities. We analyzed the 12 excerpts that describe knowledge-intensive tasks, resulting in allocation, evaluation, classification, diagnosis, modeling, monitoring, and prediction tasks. Some tasks' automation speeds up the system or improve it with previously unavailable services. Some tasks are associated with the repression of scientific misconduct. The innovations are discussed as a symptom of software's transition from mere virtualization to dynamic collaboration with people, and from technocentrism to sociotechnological functioning, in which software supports human decision-making instead of replacing it

Parameterized Complexity of Equitable Coloring

A graph on $n$ vertices is equitably $k$-colorable if it is $k$-colorable and every color is used either $\left\lfloor n/k \right\rfloor$ or $\left\lceil n/k \right\rceil$ times. Such a problem appears to be considerably harder than vertex coloring, being $\mathsf{NP\text{-}Complete}$ even for cographs and interval graphs. In this work, we prove that it is $\mathsf{W[1]\text{-}Hard}$ for block graphs and for disjoint union of split graphs when parameterized by the number of colors; and $\mathsf{W[1]\text{-}Hard}$ for $K_{1,4}$-free interval graphs when parameterized by treewidth, number of colors and maximum degree, generalizing a result by Fellows et al. (2014) through a much simpler reduction. Using a previous result due to Dominique de Werra (1985), we establish a dichotomy for the complexity of equitable coloring of chordal graphs based on the size of the largest induced star. Finally, we show that \textsc{equitable coloring} is $\mathsf{FPT}$ when parameterized by the treewidth of the complement graph

Modelagem CESM para um sistema de recomendações: o caso de uma livraria virtual

Recommender systems aim to create personalized recommendations for guiding the user in choosing the most useful product, service, or content in a large space of possible options. Through content filtering and collaborative filtering, a recommender system can select appropriate options for the user, alleviating the information overload in the context of virtual bookstores. In this sense, this work’s aim is to present the modeling and analysis of a recommender system for a virtual bookstore seen as a sociotechnological system. A sociotechnological system involves human agents and artificial agents, the interconnections between them, their interaction dynamics, subjection to changes in relation to environmental demands and the emergence of behaviors. In this context, the methodological approach is based on the systemic view of Mario Bunge, through the application of the CESM model, according to which a system can be represented by its components, environment, structure, and mechanism. Mechanisms involved in the recommender system are outlined as cause-effect diagrams. The CESM modeling offers an integrated view of the interconnections and interactions between the components of the system and their context, and the identification of the involved processes. The modeling study precedes its computational implementation and actions for improvements and corrections of non-functional aspects related to the mechanisms can be designed before its deployment in the context of a virtual bookstore