Social media has boomed in recent years, along with platforms for user generated content. Major social network platforms like Google and Facebook use a singular advertisement mediation service, where ads are provided by corporates to target users/customers. Facebook analyses and uses a userís meta data and content consuming behavior to present the best suitable commercial. We, in this work, show an innovative approach where advertisement mediation is done using userís own generated content, in the form of memes on a corporate. Memes are chosen as a medium due to their supreme ability to penetrate the internet and get viral quickly. Because the content is generated by the user, who is also the target of the advertisement, the content is well understood, received and appreciated in comparison of content used in other approaches like Facebook audience network, Google Adsense or Twitter MoPub. Using this method, users are renumerated monetarily for the content they post, which also becomes the advertisements that will be later used by corporates. We track user generated content, for subscribed corporates using Tesseract algorithm for optical character recognition along with Vader NLP. for NLP. and provide results that strongly suggest why the method suggested in this article is useful and advantageous compared to other methods.
Online Advertizements, Social Network based Marketing, Optical Character Recognition.