Building a Social Media rating model

Abstract

Social Media (SM) data are growing, and SM is becoming an acceptable part of daily life for billions of people around the world. Extracting information from Social Networking Sites (SNS) can provide great challenges as well as opportunities. Using SM data beyond day-to-day communication can provide additional values. There is much research and many products that are dedicated to take SNS beyond communication channels. In our research, we are going beyond specific tools inherent to the SM tools, such as Hashtag mentions and Like counts. Instead it will use text-based modeling, data mining techniques, natural process language, machine language, etc. to understand SM content to produce numeric ratings. The final contribution of this research is building a SM users' rating model for an event using SM data. At this point of our research, we are laying out a road map.