I think you're probably correct, but "poor" is much too generous a description of such a methodology. It rates at least an "awful", and "garbage" is not unwarra

I think you're probably correct, but "poor" is much too generous a description of such a methodology. It rates at least an "awful", and "garbage" is not unwarranted. Consider that it is only an accident of fate that there was merely 1 Drupal posting at time 0. If there had been two, I guess the entire trendline would be half as big. Or consider this even wackier example: http://www.indeed.com/jobtrends?q=ruby%2C+mongodb&l=&relative=1 http://www.indeed.com/jobtrends?q=ruby%2C+mongodb&l=&#38... This goes to show that the algorithm is at least smart enough not to explode when dividing by zero. (There were, I'm pretty sure, zero mentions of "MongoDB" in job postings in 2005.) But, then, what does this graph measure? What are we dividing by for MongoDB? The number of postings at some arbitrary later time?