Why Social Media Data Needs Sifting and Sorting?

With social media data being generated in massive amounts, the companies need to be careful with the datasets they choose from as it can be unstructured and can result in wastage of resources.

FREMONT, CA: More data has been generated in two years than in the entire history of the human race, and within another five years there will be more than 50 billion smart connected devices in the world say experts of the field. It is natural, considering the sheer amount of people on the planet and each one of them having everything they do, saved as a post for perpetuity on social media.

Social media is a global phenomenon, which contains untapped data in massive volumes. A few popular sites and regionally dominant platforms, to extract data from, each culture has its social media nuances. The incorporation of social media data adds substantial value to a variety of utilities in any research. But which of these sources are relevant? The factors that affect the solution to this problem are innumerable; hence, only the relevant ones are considered, depending on a specific use case.

Data extracted from these sources are unstructured and cannot be run in machine learning algorithms without mining it first. Even though the unstructured data is extracted abiding today’s compliance, licensing, and technical perspective, it cannot be used to obtain helpful insights without mining.

There are viable options to sort, identify, and index the unstructured data in a structured way to deliver some value for it. But only the standardized datasets support business intelligence algorithms and predictive models.

Social data is a bare necessity and should be handed to a business after it has been mined and sorted so that analytics systems can do their respective work. Even if the company is massive and possesses full vertical integration to conduct internal miming, it is still probably not worth it.

With the advancements in ML, the ability to analyze data has improved, resulting in useful data coming in for analytics. As the whole world is online, it is best for the companies to be positioned to celebrate the digital tomorrow, allowing practices that make the best use of all the information.