What are the units of dissatisfaction used throughout the page? How do they map to the y-axis of the dissatisfaction graph? What sense of scale do I need to hav

What are the units of dissatisfaction used throughout the page? How do they map to the y-axis of the dissatisfaction graph? What sense of scale do I need to have to understand the units? Is a 945 bad? How bad? Is hate linear? Since AAPL scores roughly half as much as AT&T does that mean that the average Twitterer hates AAPL half as much? What happens if someone scores a perfect 1000? Can they be hated no further? What time zone is the next update measured in? What makes your classifier 'Bayesian' besides just using something called a 'Naive Bayes Classifier'? What is the 90% accuracy determined from? Why should I care? Is a 24-hour improvement in customer satisfaction a significant thing? How quickly does hate fluctuate? What is your uncertainty in each of these measurements? Is there an overall brand hate level that I can compare these things to? How are they affected by overall sentiment toward companies? ------ It's an interesting complementary site to your primary interest in Groubal. I'm just a skeptic to methods in sentiment analysis in general. To analyze data properly is very hard. Applying tools to observe what happens is still interesting though. But I'm not sure I learned a whole lot to see graphs proclaiming that Twitterers dislike AT&T, Time Warner, Banks, Internet Providers, and Zynga. Tylenol and Enterprise were interesting to find though. I have no idea what it means for Tylenol to be 100 units less hated though. So perhaps what you should tune your ML stuff to seek out is not just some difficult to quantify measure of dissatisfaction, but instead look for things like Tylenol and Enterprise where people might not expect themselves to have such trouble with the brand. In such a case, it becomes automatic, insightful rabble-rousing instead of methodologically sparse hate-ranking.