About Hackermoods

Hackermoods uses sentiment analysis to figure out if a set of comments on a Hacker News story is relatively positive, negative, or neutral.

In general, sentiment analysis is hard. It's not great at picking up things like sarcasm and idiom, or reading into subtext. But looking at trends over time within a single group/community helps control for those errors. In other words, claiming "these comments are positive" is dangerous, but claiming "these comments are more positive than yesterday's" is more reliable. So we've designed hackermoods with the latter mentality.

The spread between positive and negative sentiment is usually more interesting than the value of the quantities themselves. Large spreads often indicate emotional topics and views. A spread that diverges can hint at a topic becoming increasingly contentious whereas a spread that converges suggests consensus.