Artificial and Natural Topic Detection in Online Social Networks

Online Social Networks (OSNs), such as Twitter, offer attractive means of social interactions and communications, but also raise privacy and security issues. The OSNs provide valuable information to marketing and competitiveness based on users posts and opinions stored inside a huge volume of data from several themes, topics, and subjects. In order to mining the topics discussed on an OSN we present a novel application of Louvain method for TopicModeling based on communities detection in graphs by modularity. The proposed approach succeeded in finding topics in five different datasets composed of textual content from Twitter and Youtube. Another important contribution achieved was about the presence of texts posted by spammers. In this case, a particular behavior observed by graph community architecture (density and degree) allows the indication of a topic strength and the classification of it as natural or artificial. The later created by the spammers on OSNs

Comparing Concept Drift Detection with Process Mining Software

Organisations have seen a rise in the volume of data corresponding to business processes being recorded. Handling process data is a meaningful way to extract relevant information from business processes with impact on the company's values. Nonetheless, business processes are subject to changes during their executions, adding complexity to their analysis. This paper aims at evaluating currently available process mining tools and software that handle concept drifts, i.e. changes over time of the statistical properties of the events occurring in a process. We provide an in-depth analysis of these tools, comparing their differences, advantages, and disadvantages by testing against a log taken from a Process Control System. Thus, by highlighting the trade-off between the software, the paper gives the stakeholders the best options regarding their case use

Leveraging Anomaly Detection in Business Process with Data Stream Mining

Identifying fraudulent or anomalous business procedures is today a key challenge for organisations of any dimension. Nonetheless, the continuous nature of business activities conveys to the continuous acquisition of data in support of business process monitoring. In light of this, we propose a method for online anomaly detection in business processes. From a stream of events, our approach extract cases descriptors and applies a density-based clustering technique to detect outliers. We applied our method to a real-life dataset, and we used streaming clustering measures for evaluating performances. Exploring different combinations of parameters, we obtained promising performance metrics, showing that our method is capable of finding anomalous process instances in a vast complexity of scenarios

A Multi-label Classification System to Distinguish among Fake, Satirical, Objective and Legitimate News in Brazilian Portuguese

Currently, there has been a significant increase in the diffusion of fake news worldwide, especially the political class, where the possible misinformation that can be propagated, appearing at the elections debates around the world. However, news with a recreational purpose, such as satirical news, is often confused with objective fake news. In this work, we decided to address the differences between objectivity and legitimacy of news documents, where each article is treated as belonging to two conceptual classes: objective/satirical and legitimate/fake. Therefore, we propose a DSS (Decision Support System) based on a Text Mining (TM) pipeline with a set of novel textual features using multi-label methods for classifying news articles on these two domains. For this, a set of multi-label methods was evaluated with a combination of different base classifiers and then compared with a multi-class approach. Also, a set of real-life news data was collected from several Brazilian news portals for these experiments. Results obtained reported our DSS as adequate (0.80 f1-score) when addressing the scenario of misleading news, challenging the multi-label perspective, where the multi-class methods (0.01 f1-score) overcome by the proposed method. Moreover, it was analyzed how each stylometric features group used in the experiments influences the result aiming to discover if a particular group is more relevant than others. As a result, it was noted that the complexity group of features could be more relevant than others

Avaliação das premissas do Programa de Reestruturação e Ajuste Fiscal e seus impactos para a situação fiscal dos Estados brasileiros

O estudo possui dois objetivos, a saber: discutir as premissas inerentes aos programas de reestruturação e ajuste fiscal (PAF) firmados entre a União e os Estados brasileiros; e propor uma equação formal da relação dívida financeira/receita que garanta para esta a convergência para a meta prevista nos contratos. Para dar conta dos objetivos realizouse revisão da legislação pertinente, a partir da qual foi formalizada matematicamente a equação de convergência. Os resultados indicam que os Estados que possuírem relação dívida financeira/receita líquida real inferior ou igual a 2,50, em 2009, tendem a cumprir a meta de redução de endividamento prevista pelo PAF, em 20 anos. Aponta-se também o desvio das hipóteses do PAF causado pela indexação da dívida ao IGP

Programa Faces: Curricularização da Extensão em um curso de Odontologia

As atividades de extensão são importantes para garantir a interação dos conhecimentos adquiridos e a prática na comunidade, tornando-se um verdadeiro diferencial na formação do estudante. O Programa de Extensão FACES foi proposto para as Atividades Extensão Curriculares (ATEX) em um curso de Odontologia. No programa foram propostos oito projetos desenvolvidos cujos  temas e públicos foram definidos levando-se em consideração situações-problemas de complexidade crescente e o ciclo de vida dos pacientes: 1º Faces da Odontologia (Jovens), 2º Dente de Leite (Crianças), 3º Harmonizar (Adultos), 4º OdontoVida (Pessoas com deficiência), 5º OdontoMais (Idosos), 6º Humanizar (Atendimento humanizado), 7º IntegraOdonto I (Pacientes hospitalizados) e 8º IntegraOdonto II (Saúde da família). O programa iniciou-se no primeiro semestre de 2021 e, nos projetos já realizados, possibilitou grande envolvimento dos alunos e abrangência das ações, possibilitando o desenvolvimento de competências indispensáveis para a formação profissional e benefícios significativos à população

A list of land plants of Parque Nacional do Caparaó, Brazil, highlights the presence of sampling gaps within this protected area

Brazilian protected areas are essential for plant conservation in the Atlantic Forest domain, one of the 36 global biodiversity hotspots. A major challenge for improving conservation actions is to know the plant richness, protected by these areas. Online databases offer an accessible way to build plant species lists and to provide relevant information about biodiversity. A list of land plants of “Parque Nacional do Caparaó” (PNC) was previously built using online databases and published on the website "Catálogo de Plantas das Unidades de Conservação do Brasil." Here, we provide and discuss additional information about plant species richness, endemism and conservation in the PNC that could not be included in the List. We documented 1,791 species of land plants as occurring in PNC, of which 63 are cited as threatened (CR, EN or VU) by the Brazilian National Red List, seven as data deficient (DD) and five as priorities for conservation. Fifity-one species were possible new ocurrences for ES and MG states