Visualizing Hacker News

Wow, how did this get discovered?<p>I'm a co-founder at EffectCheck and I was working closely with Scott this weekend as he was building this. It wasn't really ready for viewing yet, but okay... :)<p>Please note that the top graph is currently a mixture of two sets of data. The older points were using a less sensitive and improperly calibrated HN comment model, hence why everything is drifting around near "Typical." The points from 14:47 onward are using the correct model.<p>For those wondering why HN was so negative from 14:47-20:47, I believe the main topics of conversation were the Bitcoin and Sega debacles. Makes sense that people were really anxious given all that news.

So cool! This is what I had started working on for the HNSearch API Contest, but I hadn't gotten far. I'm SO glad someone did this. I feel as though this could be made into a useful and viable product, if marketed correctly and accurate enough.

See also Rob Hawkes’ (from Mozilla) attempts to map Twitter sentiment:<p><a href="http://rawkes.com/blog/2011/04/19/finding-patterns-in-twitter-sentiment" rel="nofollow">http://rawkes.com/blog/2011/04/19/finding-patterns-in-twitte...</a>

interesting idea. Doc here. I would organize them as<p>1. Depresssion 2. Anxiety 3. Hostility 4. Happiness 5. Confidence 6. Compassion<p>Anxiety and Depression <i>definitely</i> go together, in the same way that hostility and happiness are actually similar in terms type of emotion, in terms of level of intellect, and confidence and compassion would be at the highest end of that spectrum.<p>I would also change the colors to group them: anxiety and depression as blues, hostile and happy as reds, and confidence and compassion as greens. Or something like that.

Wow, I slept through this whole thing. I'll be around now though. If anyone has any requests for different ways to interact with the data, let me know and I'll work on getting it added to the site.

Too bad the EffectCheck API is not open for all. Looks like a well-parameterized sentiment analysis tool. What does this page tell us: <a href="http://effectcheck.com/pricing" rel="nofollow">http://effectcheck.com/pricing</a><p>It can be used for a stock analysis and dampening or amplification caused from other firehose like sources like Twitter.

are you also behind the <a href="http://www.wefeelfine.org/" rel="nofollow">http://www.wefeelfine.org/</a> project?<p>It was neat when it came out years ago... Although still not sure how to make any meaningful use of this tool. I suppose it is more useful for content generators..

I'll be adding the link to the site once I get home from work today, but I've set up a mailing list for anyone who might be interested in getting an email when new features are pushed out: <a href="http://eepurl.com/emtQU" rel="nofollow">http://eepurl.com/emtQU</a>

Can it work farther back in time? interesting if there are longer term trends. Happiness particularly can be indicative about the overall satisfaction from HN.

Do you expose the underlying data? For example, what are the most hostile articles about Microsoft?

It'd be nice to also see typical comments both with high and low scores in each category.

it'd be cool to integrate it with <a href="http://smood.it" rel="nofollow">http://smood.it</a>