Social Networks Like Facebook Are Finally Going After The Massive Amount Of 'Unstructured Data' They're Collecting

The future of social media turns on being able to make sense of "unstructured data," the firehose of texts, posts, tweets, pictures, and videos that even the most powerful computers are unable to classify.

Why is this important? Because social networks have only mined the tip of the iceberg in data terms- information such as likes, dislikes, occupation, location, and age.

That leaves a lot of other social activity that hasn't been parsed yet. More than 90% of social data is unstructured.

In a new report from BI Intelligence, we show how social networks are in a race to innovate in areas like "deep learning," cutting-edge artificial intelligence research that attempts to program machines to perform high-level thought and abstractions. These advances are helping social networks and their advertisers glean insights from this vast ocean of unstructured consumer data. Thanks to deep learning, social media has the potential to become far more personalized. New marketing fields are quickly emerging, too: audience clustering, predictive marketing, and sophisticated brand sentiment analysis.

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Here are some of the key takeaways from the report:

• Seventy-one percent of chief marketing officers around the globe feel their organization is unprepared to deal with the explosion of big data over the next few years, according to an IBM survey. They cited it as their top challenge.
• Targeted and personalized marketing using social data is expected to be the business area that benefits the most from mining big data - 61% of data professionals say big data will overhaul the practice for the better, according to Booz & Company.
• Facebook ingests approximately 500 times more data each day than the New York Stock Exchange (NYSE). Twitter is storing at least 12 times more data each day than the NYSE.
• By deciphering image and video-based data, marketers will be more effective and comprehensive in their "social listening" efforts. Large companies spend a great deal of money monitoring people's attitudes toward a specific brands or product, and despite all the photo-and video-sharing happening on social media, these mediums were formerly mostly invisible to their analytics tools.

In full, the report:

• Provides an easy-to-understand explanation of artificial intelligence and the various subsets of the field that are applicable to social media data.
• Includes interviews with artificial intelligence experts that reveal how advanced machine learning systems are today, and how different social networks are leveraging this powerful technology.
• Unpacks which types of social media data will be filtered through machine learning and how difficult it will be to process the different kinds of data.
• Gives examples of how artificial intelligence will improve social media ROI and revolutionize digital marketing and advertising.