Análise das tendências e concentrações criminais no município do Rio de Janeiro, com foco nas áreas de atuação territorial da Força Municipal e na comparação entre os dados de 2023–2024 e 2025.

Tutorial for microclimlearn package

Sitka spurce

Online personal-finance communities increasingly shape how users seek advice, evaluate credibility, and make sense of financial uncertainty. Yet computational studies of online financial discourse often classify posts by topic, risking a construct-validity error: financial topics do not, by themselves, reveal what kind of information support users seek, whom they trust, what risks they perceive, or how peer communities evaluate financial claims. This study examines high-visibility discussions in r/phinvest, a Philippine-oriented Reddit community, as public episodes of everyday financial information seeking and peer sense-making. Using a qualitatively driven sequential mixed-methods design, the study combines exploratory corpus mapping with directed qualitative content analysis. Topic-domain mapping, flair analysis, term frequencies, local-term detection, and exploratory topic modeling are used to organize the corpus, while qualitative coding provides the main basis for interpreting information-need types, uncertainty objects, trust objects, risk frames, peer-response types, and Philippine contextual anchors. The corpus consists of 30 high-visibility r/phinvest threads through June 30, 2026, including 5,298 parsed comments and 5,328 mapping-eligible post/comment documents. Findings show that high-visibility r/phinvest discourse spans business, investing, real estate, insurance, banking, digital finance, and government-linked funds, but these topic domains are analytically insufficient. The same financial topic can express different information needs, including procedural guidance, product comparison, trust verification, risk assessment, decision validation, and experiential advice. Peer responses function as informal credibility evaluations through warnings, corrections, calculations, anecdotes, recommendations, and referrals. Philippine-specific institutions and products, including VUL, MP2, SSS, BSP, PDIC, GCash, Maya, Pag-IBIG, and UITFs, localize financial uncertainty and shape how users evaluate safety, legitimacy, suitability, liquidity, and trust. The study contributes to information behavior, financial capability, and computational text-analysis research by showing why financial topics must not be treated as direct evidence of information needs, social importance, or financial behavior.

Shiny App Presentation

The documents displays most used codes in R for data analysis and visualization.