VideoStance

VideoStance extracts claims from knowledge video transcripts and cross-references them across multiple creators to surface consensus, controversy, and unique insights — all attributed to the original source. Unlike single-video summarizers, VideoStance requires at least 3 independent creators per topic to produce a meaningful cross-analysis. The automated pipeline segments transcripts, extracts structured claims with stance labels (support/oppose/neutral) and timestamps, then cross-references them to identify where creators agree (consensus), where they disagree (controversy with both sides presented), and what only one expert noticed (unique insight). Current coverage spans AI coding tools (Cursor, Claude Code, Codex, Copilot), LLM comparisons (ChatGPT vs Claude vs Gemini, GLM 5.2 vs DeepSeek V4 Pro), and technology investing — sourced from both YouTube and Bilibili creators. Every hub page includes spec tables, scenario-based recommendations, and automatically generated FAQs derived from the claim data. Key use cases: Tech buyers tired of single-source influencer takes Developers choosing between AI coding tools Investors tracking divergent expert opinions on AI models Content researchers mapping claims across dozens of videos