Comment by pedalpete | Hacker News Reader

Comment by pedalpete | Hacker News Reader

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Is the knowledge graph weighted more to submissions than comments? I'm surprised to see how generalized the keywords associated with my user are "Company, Product, Market, Part, Article, Issue, Bit".

I'll admit, I am a generalist, and I comment more than I post, but I would have thought/hoped my knowledge base would trend towards neurotech, sleep, mental health, health, wellness, etc, as I feel that is the "less general" stuff I comment on.

Though I recognize this is how I like to see myself, I do often comment on business models, branding, etc etc, which are areas I have interest in.

I wonder if topics that have more activity from a user, but are in a less popular topic area would improve this?

Right now it does end up representing quantity + quality than just quantity alone. How can we do better?

How are you measuring quality?

I'm thinking you'd have a huge volume of people with similar common attributes, and if these most common attributes/keywords suggest a more baseline understanding of the community as a whole.

I'm not sure how you surface the more nuanced understanding of each users knowledge or interests.

The few things I'm thinking are 1) more weight to more recent content than earlier. We change and grow as people. I used to be in the music industry, then 3d mapping, and now neurotech. My music experience is now old, but neuro is fresh. That may be more interesting/valuable.

2) commonality with the viewing user. Where do we overlap, and again, where do we overlap where others don't? How often would a person be searching for someone whom they don't have overlap with? We are likely interested in the same things. Though perhaps somebody who knows nothing about marketing, is looking for marketing help, so I'm not sure how you surface that.

I guess I'm wondering what you imagine the ultimate use case being? Or the early adopter use case. You may be prioritizing the algorithm for uses I'm not expecting.

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