Semantic Analysis: In addition to counting and analyzing the data structure from Twitter, R-SHIEF also analyzes the semantic nature of the words in teh tweets themselves. Each row of tweets will have a correlating array of attributes such as language(s), good 1-5, bad 1-5, acronym, meme, first name, last name, place, thing, etc. Using swarm computing and crowdsourcing platform, R-SHIEF is able to arbitrarily generate that data from the tweet data for various time scopes so it could actively maintain one for the last 10 minutes, the last hour, the last 6 hours, the last 12 hours, the last 24 hours, and forever.