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What is HN thinking? Real-time sentiment and concept analysis

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Hi HN,I made Ethos, an open-source tool to visualize the discourse on Hacker News. It extracts entities, tracks sentiment, and groups discussions by concept.Check it out: https://ethos.devrupt.ioThis was a "budget build" experiment. I managed to ship it for under $1 in infra costs. Originally I was using `qwen3-8b` for the LLM and `qwen3-embedding-8b` for the embedding, but I ran into some capacity issues with that model and decided to use `llama-3.1-8b-instruct` to stay within a similar budget while having higher throughput.What LLM or embedding would you have used within the same price range? It would need to be a model that supports structured output.How bad do you think it is that `llama-3.1` is being used and then a higher dimension embedding? I originally wanted to keep the LLM and embedding within the same family, but I'm not sure if there is munch point in that.Repo: https://github.com/devrupt-io/ethosI'm looking for feedback on which metrics (sentiment vs. concepts) you find most interesting! PRs welcome!

HN · launched Feb 12, 2026 · 37 upvotes (top 23%) · 0 views

Niche: sentiment analysis software · 32 launches, 0 in the last 7 days · Explore this niche →

Category and tags

  • Horizontal
  • Analytics & BI
  • Prosumer
  • AI feature
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes Fetching public Hacker News API data, processing text through an LLM or embedding model, and displaying cluster charts via a static web app can be built quickly with vibe coding.

Discussion

20 comments analyzed.

Concerns raised: Sentiment analysis is unsophisticated and sloppy, Entity tracking produces inaccurate sentiment results, Limited context window eating prompts and increasing costs, Information not properly sent to prompt for comment hierarchy, Green colors in sentiment visualization not distinct enough

Feature requests: Expand historical data back to 2007, Improve prompt engineering for sentiment analysis, Better concept naming and disambiguation guidance in JSON schema, More sophisticated multi-level comment hierarchy processing, Improve entity tracking accuracy for better sentiment attribution

Competitors

Other products that read as similar to this one : 132 launches clear the similarity bar, closest 8 shown.

Attention rank: #46 of 133 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 106 days after the earliest competitor.

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