Cutting through social data noise with machine learning

All of us that work with social data know the signal to noise ratio is ever increasing, and not in our favor. As the irrelevant baby picture or the 1000th Trump meme pops up in our social, that micro-dopamine hit of ingesting content from social media may not fire like it used to, and you lose interest. In fact, it is this increasing noise that can cause businesses to become disillusioned or skeptical that they can use social data to achieve their goals. As these noise levels increase, it's not hard to recognize that businesses need ever more powerful tools to find those sparkly signal-diamonds in the social rough. The basics of attributing sentiment scores and broad topic categories are outgrowing their usefulness and competitive advantages to drive significant results.