Social media has become a big part of the Internet. Many social media companies exist that allow users to post and share information to their network of friends. Companies and brands constantly search for opportunities to use such data to increase brand value. Monetizing on that data however, can be troublesome and burdensome because of the vast amount of data that need to be sifted through. One challenge faced by brands is that many attributes of an audience (such as gender, ethnicity, age, etc.) that is talking about a brand or topic on social media are hidden by the author because of privacy concerns.
For marketers and advertisers, analyzing demographic information concerning a target audience can provide valuable information. Knowledge of the demographics of a crowd of people at a venue such as a stadium can be very helpful in selecting appropriate advertisements to display to the crowd. Knowledge of the demographics of people reacting to a marketing campaign on social media can be helpful in market research. In other fields as well, obtaining accurate insight into individuals' behavior, of economic activity, etc., can provide useful information. Many companies and organizations frequently generate predictions for such unknown variables based on one or more known variables. However, in many instances obtaining accurate predictions for a desired item of information can be difficult. In many existing systems, simplistic assumptions are made to generate a prediction, often producing inaccurate results.