Desinformação na mídia: análise exploratória de conteúdos jornalísticos veiculados no Portal G1

Trabalho em formato de Resumo Expandido

Violence against women in the state of Goiás based on analysis of digital media: a case study on the G1 news portal

A violência contra a mulher é uma realidade no Brasil. Embora o país tenha avançado no âmbito da legislação, se destacando a Lei n. 11.340/2006, Lei Maria da Penha, e a Lei 13.104/2015, conhecida como lei do feminicídio, ainda existem muitos desafios no enfrentamento à violência contra a mulher, os quais perpassam por questões legais, sociais, culturais e políticas. Um dos pontos que chama a atenção é que nem todo crime é denunciado, o que acaba por impactar na consolidação de indicadores sobre violência que possam ser utilizados na construção de políticas públicas de apoio à mulher e enfrentamento à violência. Além disso, ainda existem obstáculos e desafios quanto ao levantamento destes dados, os quais são, em sua maioria, obtidos junto às polícias civil e militar de cada estado da Federação, as quais utilizam estruturas e metodologias distintas para aferição deste fenômeno social. Por outro lado, é notável a repercussão dos casos de violência contra a mulher na mídia, o que abre a oportunidade de exploração das notícias como fontes de dados. Este artigo explora o uso de soluções de mineração de dados voltadas à identificação de temáticas exploradas no contexto da violência contra a mulher a partir de peças noticiosas veiculadas em mídia digital de modo a buscar um entendimento de posicionamentos e articulações nas narrativas observadas. Para tanto, é realizado um estudo de caso sobre uma amostra de textos jornalísticos extraídos do portal de notícias G1 Goiás. Os resultados obtidos sugerem padrões, em termos de temporalidade e temáticas exploradas, e destacam a questão da invisibilidade da violência doméstica contra a mulher e exacerbação das situações extremas, incomuns e ditas espetaculares.Violence against women is a reality in Brazil. Although the country has advanced in terms of legislation, with emphasis on Law n. 11,340 / 2006, Lei Maria da Penha, and Law 13,104 / 2015, known as the femicide law, there are still many challenges in confronting violence against women, which permeate legal, social, cultural and political issues. One of the points that draws attention is that not every crime is reported, which ends up impacting the consolidation of indicators on violence that can be used in the construction of public policies to support women and fight violence. In addition, there are still obstacles and challenges for collecting this data, mostly obtained from the civil and military police of each state of the Federation, which use different structures and methodologies to measure this social phenomenon. On the other hand, the repercussion of cases of violence against women in the media is notable, which opens up the opportunity to explore the news as data sources for generating indicators. Based on this, this paper explores the use of solutions based on data mining techniques aimed at identifying themes explored in the context of violence against women from news items broadcast in digital media. Therefore, a case study is carried out based on a sample of journalistic texts extracted from the G1 Goiás portal. The results obtained suggest patterns, especially with regard to temporality and the themes explored, in addition to highlighting the issue of (in) visibility of the topic in digital media

Análise ergonômica do trabalho no setor de cargas de tijolos e telhas em uma indústria de cerâmica de Catalão - Goiás / Ergonomic analysis in the brick and tile loading sector in a ceramic industry in Catalão – Goiás

A atualidade é marcada por um novo conceito de trabalho, que agora passa a se preocupar com o aumento da expectativa de vida, consciência de que é fundamental adquirir novos hábitos e estilos de comportamento, responsabilidade social e compromisso com o desenvolvimento sustentável, bem como com a qualidade de vida dos seus colaboradores. Aumentar a produtividade deve estar associado a melhorias de condições do ambiente, especialmente no que se refere à segurança do trabalho, com adaptações ergonômicas e uso de equipamentos de proteção individual adequados, evitando, com isso, riscos de doenças ocupacionais e/ou acidentes. E, por ser uma atividade praticada desde a antiguidade, a qual faz uso direto da mão-de-obra humana, a cerâmica é o foco deste estudo. O objetivo deste trabalho é analisar aspectos ergonômicos do processo de carga de tijolos e telhas numa indústria de cerâmica do sudeste goiano, da cidade de Catalão, Goiás. Para a concretização deste estudo, foi realizada uma pesquisa de campo. A partir do estudo, concluiu-se que a empresa prioriza se destacar no mercado regional, com foco principal na geração de lucros, porém com inobservâncias no contexto da segurança de seus funcionários e na prevenção de acidentes e doenças ocupacionais

INCÊNDIOS NA AMAZÔNIA A PARTIR DE UMA PERSPECTIVA DE CIRCULAÇÃO DE TWEETS

Forest fires are one of the main threats to biodiversity in the Amazon region. Official data revealed record numbers in the volume of fire outbreaks in the year 2022. This worrying scenario reverberates not only in political and governmental issues of environmental preservation, but also in social networks, where society exposes and debates its views and opinions. This paper presents an exploratory study on a set of tweets in Portuguese related to the fires in the Amazon. Computational solutions are used to generate results that allow the thematic identification of the content conveyed by Twitter users on the subject. The results revealed a polarization on the issue, going beyond environmental problems and going against political and affective issues.Los incendios forestales son una de las principales amenazas para la biodiversidad en la región amazónica. Datos oficiales revelaron cifras récord en el volumen de focos de incendios en el año 2022. Este preocupante escenario repercute no solo en temas políticos y gubernamentales de preservación ambiental, sino también en las redes sociales, donde la sociedad expone y debate sus puntos de vista y opiniones. Este artículo presenta un estudio exploratorio sobre un conjunto de tuits en portugués relacionados con los incendios en la Amazonía. Se utilizan soluciones computacionales para generar resultados que permitan la identificación temática de los contenidos transmitidos por los usuarios de Twitter sobre el tema. Los resultados revelaron una polarización sobre el tema, yendo más allá de los problemas ambientales y yendo en contra de lo político y lo afectivo.Os incêndios florestais são uma das principais ameaças à biodiversidade da região amazônica. Dados oficiais revelaram números recordes no volume de focos de incêndios no ano de 2022. Esse cenário preocupante se reverbera não apenas nas questões políticas e governamentais de preservação ambiental, mas também nas redes sociais, onde a sociedade expõe e debate suas visões e opiniões. Neste artigo é apresentado um estudo exploratório sobre um conjunto de tweets em língua portuguesa relacionados aos incêndios na Amazônia. São utilizadas soluções computacionais para a geração de resultados que possibilitaram a identificação temática dos conteúdos veiculados pelos usuários do Twitter sobre o assunto. Os resultados revelaram uma polarização sobre a questão, extrapolando os problemas ambientais e indo de encontro a questões políticas e afetivas

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost