> For the complete documentation index, see [llms.txt](https://yourcomments.gitbook.io/home/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://yourcomments.gitbook.io/home/sentiment-analysis-disclaimer.md). # Sentiment Analysis Disclaimer ### Sentiment Analysis Discussion and Disclaimer There are a near-infinite number of services, protocols, approaches, and AI and ML (machine learning) tools. We decided on KISS (Keep It Simple Stupid). Tldr: We return basic polarity. The CCE is focused on the following goals: Capture, basic scoring, usable data, and having fun. We have... * Proof of concept and delivery of a working system * Collection of comments and delivery of normalized sentiment analysis * Delivery of data that works with data science, business analysis, and AI/LLM tooling * Customer support and a collaborative environment to build the best tools #### Generative AI is Nondeterministic The current generation of AI is often hardly intelligent and, by certain metrics, very artificial. Nevertheless, it is a miraculous tool that makes this project possible\*. Regardless of your opinion, AI is a nondeterministic system. Rerun the same comments and get slightly different results. Additional refinement of tooling, training, and supplemental services (such as RAG, agents, or multi-pass analysis) can improve the results. The best results we have found come from aggregate analysis. Our strengths are trends, user behavior over time, and content-to-response relationships. One report is interesting, but a month's data is revolutionary. **Let’s talk about the future** We will be adding CTA (call-to-action) extraction very soon. Similar to CTA extraction, broadcast-quality analysis is a possibility (review comments for issues in audio, video, or production quality). The CCE team sees several easy-to-generate statistics in the data we are collecting that help better understand audience behavior. We are exploring subjectivity/objectivity identification, intensity ranking, emotion detection, simple grading analysis alternatives, aspect-based SA, and other approaches. We want to invest in the best code and services, so these discussions are ongoing. Thank you for your attention to this matter We are just getting started! The CCE/YourComments.ai team is excited to work with you! \* We did not vibe code the platform. The one time we let an agent into the codebase, it destroyed the application and took over a week to recover. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://yourcomments.gitbook.io/home/sentiment-analysis-disclaimer.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.