The fundamental problem with social media sentiment analysis is that it is based upon the assumption that tweets are representative of the population. It ignores the issue that a large percentage of tweets come from spam bots.<p>As soon as you start measuring sentiment, there is an incentive for an interested party to try sway the results. For example, I could use a spam network to publish opinionated tweets just to obtain a headline in the media (E.g., "95% of tweets agreed with X"). The media coverage gives legitimacy to the manipulated result.<p>I wonder how many companies have set goals around this sort of sentiment. "Let's increase positive sentiment by 10%". An ethically challenged consultant could easily manipulate results to meet the stated goal.<p>There is still a place for sentiment analysis and that is in targeting individuals for follow-up. Assuming that the user can be matched to a real consumer, this avoids the issues of statistical manipulation. Though users can still exploit the "complain and get something free" loophole.
When you know the right pieces to the puzzle, amazing things can be created. Thanks for taking the time to show even more cool tools for future tinkering!