Since the inception of social networks they’ve been a window into the outside world while also serving as a medium for current and future friends to connect. They’re a magical place but also come with some downsides, especially for large companies intent on maintaining an immaculate brand image.
The fact is, social media is just that – social – and it’s one of the first places people go to voice their opinions on everything from music to sports to dissatisfaction with the lunch they just had. And when things go sideways they spiral out of control quickly, which is why a majority of large companies use online brand reputation management tools on a regular basis.
But as social media evolved and the sheer number of conversations taking place skyrocketed, it became clear that conventional approaches to analyzing social media threats to brands by primarily looking at keyword combinations just wasn’t cutting it. And that’s where machine learning comes into play.
For example, think about the difference between running random searches for combinations of keywords in Google and it knows nothing about you (your habits, interests, etc.) versus using machine learning to provide more tailored, valuable results. Well that’s exactly why Google integrated machine learning into their search engine a few years ago so they can learn from inputs that will then drive higher quality outputs.
When it comes to improving social media brand reputation management technologies, machine learning and in particular deep learning (what our company specializes in) will be the breakthroughs that allow large companies to cut through the white noise and discover actionable insights. The sooner potential issues are found the quicker they can be addressed, thus mitigating damage.