Content noise in social media monitoring is undoubtedly the biggest challenge facing most brands. Whether your company is monitoring your brand, product, or a competitor or two, getting a “clear signal” within the social media sphere is a critical first step.

Getting rid of noise in social media is an art and a science

In social media, a term like “HP” is used to describe a number of subjects aside from Hewlett Packard, more often automotive “horsepower” and the book/movie/toy “Harry Potter.”  So if you’re trying to listen for HP computers but you keep getting false-positive mentions about cars and teenage wizardry, you’re not alone. It takes a lot more than a simple boolean search and a list of word exclusions to get rid of the noise that has nothing to do with the subject you want.  When setting up a search, it’s important to combine brand phrases along with product concepts and product attributes that can help the system to identify relevant mentions.  Yes, this can be a painstaking manual process with literally 100’s of keyword inclusions and compounded keyword inclusions, but is usually required to filter out the noise.

We took a different path and developed some pretty slick technology that uses semantic filtering to get rid of the noise, so it does the filtering automatically, neat.   All brands have their unique social media monitoring challenges, “HP” being one, I’d love to hear about other brands with these heavy noise problems too…