FP Canada Research Stage 2

<p data-end="1383" data-start="747">This second deliverable builds on the web-data protocol (Deliverable 1) and presents the <strong data-end="860" data-start="836">substantive findings</strong> from topic modeling and sentiment analysis of consumer narratives about financial planning. Using a cleaned corpus of short, real-world comments from multiple online platforms, the report analyzes both a broad sample of public voices and focused subsets that highlight (1) people who explicitly say they do <em data-end="1173" data-start="1168">not</em> use financial planners or advisors, (2) individuals who mention low income, poverty, or financial hardship, and (3) Canadian consumers, including those referencing products such as RRSPs, TFSAs, and CPP/QPP.</p>

<p data-end="2071" data-start="1385">Through LDA topic modeling and qualitative interpretation, the report surfaces recurring themes such as: “It’s too expensive,” “I don’t trust the system or the advisors,” “I can manage on my own,” and “I feel ashamed or judged.” A second thematic map zooms in on low-income and financially vulnerable groups, showing how many perceive planning as something “for rich people,” feel that advice does not fit their unstable reality, or experience practical access barriers. Each theme is followed by <strong data-end="1916" data-start="1882">practice-oriented implications</strong> for planners and organizations (e.g., fee transparency, scaled service models, non-judgmental communication, partnerships with community organizations).</p>

<p data-end="2335" data-is-last-node="" data-is-only-node="" data-start="2073">The document is structured in three parts—an executive summary, a practitioner-focused comprehensive report, and a detailed analytic/technical appendix—so that researchers, policymakers, and practitioners can all use the findings at the level of depth they need.</p>

<p data-end="2335" data-is-last-node="" data-is-only-node="" data-start="2073">This project relies exclusively on publicly available big data collected from open web sources via web crawling. Because no identifiable human subjects data are included, this work did not require IRB review.</p>