We have developed an application that helps users to tailor a message to a particular audience. It uses a message resonance model that rates the wording of a message based on an analysis of millions of pieces of data with regard to their historical success in the context of a target audience. We have shown that higher resonance messages are twice as likely to be retweeted. Based on a semantic concept expansion component, our application is able to find similar words that resonate better in the same context and propose word replacements to improve the overall likelihood of success.
For this demonstration, we are using Twitter messages and an audience of Cloud Computing experts and enthusiasts. Links to the Web application and supporting material are available from http://swc14.pablomendes. com. The username is `reviewer2' and the password is `gardacheluna' (without quotes).